Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:10):
Hello and welcome back to the how to Get an
Analytics Job podcast.
So today we're going to betalking about the importance of
building industry friends andthe amount of opportunities that
can bring you.
I'm also going to be talking tomy guest about SQL what you
need to know, what's the bestway to learn it and how does it
show up in a day-to-dayworkforce.
(00:31):
And then also she is going andgetting an MBA to advance her
analytics career.
So our guest is Molly, who,coincidentally, is actually the
first person back.
What was it five years ago?
Yeah?
Five years ago, five years agoGetting getting.
I helped you get your firstanalytics job.
Um.
So I know some of the guestshave probably you've been on
(00:57):
quite a few times over the yearsyeah, there was an episode with
Gary Fly.
Speaker 3 (01:01):
Yeah, um, and I'm not sure if that was my only
episode or not, but I doremember that one specifically.
Speaker 1 (01:07):
Yeah, well, I feel like you've been on In the chats
heavily.
Yeah.
Speaker 3 (01:11):
Yeah, the YouTube chats.
Speaker 1 (01:13):
Yeah, yeah.
Well, you're a great kind ofresource that I can like.
I want people like you becauseI mean, you can't see it, but we
got a Greensboro Collegestudent kind of running behind
the scenes, craig, over there.
Craig's killing it.
Just like having someone that'sfive years into their career
interacting with someone who'slooking to get their foot in the
door.
Like you were saying off airthat you were a little bit
(01:36):
nervous, but like just givingyour authentic opinion about you
know what's been yourexperience is hugely insightful
for someone like Craig.
Speaker 3 (01:46):
Yeah, I mean I really , I would just say jump into it.
Speaker 1 (01:51):
Yeah.
Speaker 3 (01:51):
You know, especially your first job, I wouldn't worry
too hard about is this theperfect fit or not, because
ultimately you're not going toknow until you start gaining
some of that experience.
Like you know, what is it thatyou're looking for in a position
.
What kind of management styledo you prefer?
What kind of workflow style?
Speaker 1 (02:09):
do you prefer what size company?
Speaker 3 (02:10):
What size company?
Speaker 1 (02:11):
You know like there's pros and cons.
If you're working in a hugecompany, you're a cog on a very
large wheel, but if you're in asmall company, you might be the
only person who knows analyticsin the entire company yeah, only
(02:31):
person who knows analytics inthe entire company.
So, and there's a lot ofin-between ground there too,
right?
Well, I mean, I guess let meask you this have you worked?
It sounds like well.
How many jobs have you had in?
Speaker 3 (02:35):
analytics over the last five years is it?
Is it two or three?
My third yeah okay, so my firsttwo were uh jumps, and they
were all so different from eachother, right?
Speaker 1 (02:43):
what, but that's like I feel like that's great advice
, though, because the first jobyou got you, I think you
probably you didn't like it, foryou don't have to be explicit,
but like X, y, z, reason.
Speaker 3 (02:54):
Yeah, so I enjoyed it .
I was working agrochemicalsfirst and doing data mining and
it was a very generous title.
I definitely learned a lot, butthere wasn't any sort of like.
I wasn't using any sort of SQL,I was using Microsoft Excel.
That's it.
Speaker 1 (03:11):
Right.
Speaker 3 (03:12):
And I got pretty good with Excel and automating
things within Excel and then Imade a big leap to.
So I stayed there for a yearand after a year I made a big
leap to a CPA firm as a datascientist, where I just was
diving right into APIs usingPython.
Speaker 1 (03:36):
Well, I guess, let me from a third-party perspective.
I remember you during that timeand you were so stressed.
I was so stressed.
So, like I hear the advice of,like you want to jump in with
both feet, there are downsidesto that approach.
Yeah, because, like you weregoing from like Excel to Python,
(03:57):
I mean from like data miner todata scientist.
Yeah, which, like I mean, kudosto you.
Speaker 3 (04:07):
I mean you like you.
Speaker 1 (04:08):
You like stuck it out and like got on top of it.
Yeah, um, because it soundslike the well.
I mean, I remember talking toyou during that time and you
were like just it was likedrinking water out of a fire
hose.
Speaker 3 (04:22):
However, I will say and I do think that this is
important, regardless of whatfield you're going into and what
type of position is just reallybeing honest about what you are
capable of.
So I had just done I think itwas like a data boot camp online
(04:42):
and did like a eBay webscraping project that I didn't
even know was technically it'snot illegal, but like you're not
supposed to do that, right?
And I was like yeah, this iswhat I can do and I'm using
Python's like or Python, thepandas library.
So I was like okay, I can, Ican clean data and kind of went
into my interview just beinghonest about that and trying to
(05:08):
be as confident as I can.
So they knew where I was at,but they were ready to be like
cool, you know how to run somecode, let's throw you into the
deep end.
But I did have a really greatboss and a lot of guidance there
, and I think it was a learningexperience that I wouldn't have
been able to teach myself on myown.
Speaker 1 (05:29):
Right.
Well, I mean, if you thinkabout it, like the
accountability there, you eitherfigure this out or you get
fired.
You know that it's a little bitmore than like oh, I found a
free YouTube resource, likethat's the accountability
there's kind of tough.
I mean, I guess you can pay forcontent or you could sign up
for like a you know college orboot camp, and like, having that
(05:50):
money on the line of like I'mpaying for this, if I don't get
it done, if I don't finish it,I'm just wasting my time and my
money.
Yeah, but you did it on likesuper hard mode.
It's like I'm going to lose myjob and my income, which I mean
that is kind of a cheat code.
(06:11):
What were you going to say?
Speaker 3 (06:12):
Well, I was going to say, to be fair, I jumped into
this position that felt veryadvanced from where I was coming
from, for sure, but I was morelike running the code and making
tweaks to it and then editing,like when the code would fail
I'd have to troubleshoot it,which was still very difficult,
(06:34):
as opposed to like I didn't getthe job and then they expected
me to write this elaborate code.
Speaker 1 (06:40):
Gotcha.
Speaker 3 (06:43):
At some point I had to do that.
That was stressful.
Speaker 1 (06:51):
It's funny because I kind of feel the same way or
similarly about SQL.
I think I built it up in myhead a little bit I don't want
to do SQL, I don't really likecoding.
But I'm realizing now because Ihave recruiters approaching me
fairly regularly and one of thequestions that keeps coming up
and up is do you have SQLknowledge?
(07:11):
And I guess, before we get intothe topic, I want to kind of
elaborate.
You can be an analyst and workin Excel.
Like financial analysts, Ithink pretty much across the
board, unless you're at like avery high level, are mostly in
Excel.
Like financial analysts, Ithink, pretty much across the
board, unless you're at like avery high level, are mostly
using Excel.
Speaker 3 (07:29):
Anything I do in SQL or Python ends up getting
exported to Excel anyway.
Speaker 1 (07:36):
So you don't have to learn SQL.
I feel like that's likesacrilege.
Like you know, you go onLinkedIn and everyone's posting
about SQL, blah, blah, blah,blah.
It's not relevant for I wouldsay, like non-tech brick and
mortar, like you know, if youwork at a grocery store, they're
probably not having the peoplethat are actually digging
(07:58):
through the data.
Most of that heavy lift isgoing to be in Excel.
There are going to be likebusiness intelligence people,
people who kind of run thebehind the scenes, but it's
mostly like a self-service towhere you have a GUI.
For example, microstrategy isan example of that.
You sign into it and then it'sgot a list of folders and it's
like all right, I want stateattribute and I want sales, and
(08:21):
then you just click and drag itin there and then hit export and
then it's in Excel.
Speaker 3 (08:26):
Yeah, and so after my data scientist position, I'm
now a data analyst, so it's kindof a funny transition there.
But now I work at a techcompany and I would say it is
very it's funny.
I'm a data analyst, but I don'tdo analytics.
Speaker 1 (08:44):
What does that mean?
Speaker 3 (08:46):
well, when I think of analytics, I think about power
bi, I'm thinking about, like,pulling all of this data and
then creating insights from it,as opposed to now, where I am, I
do a lot of tech support, I doa lot of data mapping, um so
like etL.
Yeah, that's like yeah.
Speaker 1 (09:08):
Essentially.
Yeah, I mean that's so.
You're basically like creatingthe sandbox in which you know an
analyst who might even be usingExcel is coming in and like
knows the business?
So there's kind of that, thatspectrum of you know.
Do you sit more within thesystems side of things or are
you more kind of in the business, influencing decisions?
Speaker 3 (09:28):
Yes, and even to like be a data scientist or do
traditional analytics, I wouldagree with you that, like you,
probably don't have to use SQLif you don't need to be
accessing these large data setsyourself, if you can get
somebody to pull that data foryou you can do all the analytics
(09:51):
outside of it for sure,especially like Tableau Power BI
.
It's funny those are tools thatI use to put on my resume and
I've done the projects but, I,would be if I went for my next
interview and they asked me if Icould you know if I use Power
BI and Tableau.
I'd say I've used it before andI feel confident that I could
(10:13):
you know, it's like riding abike.
Speaker 1 (10:16):
Yeah, Well, I mean, BI tools are like.
Speaker 3 (10:18):
I don't know, it might take me a while.
Speaker 1 (10:20):
Well, I mean, it's kind of 80-20, right, like
there's in Power BI or Tableauor whatever.
I'm confident that if I gaveyou an hour, you could probably
connect to a data set, pull itin and build out a very simple
interactive dashboard Like it.
You know, maybe an hour is liketoo zealous.
Speaker 3 (10:43):
Maybe if I gave you a day, I did make a map at my
current position that ended upnot being used at all, but that
was kind of relearning it, whereI think I spent an hour at
least relearning how to do it.
But then, once the data was inthere, it took about 15 minutes
to make the map.
Speaker 1 (11:03):
Yeah, I was about to say it's more of a refresher.
It's so much easier, if you'vealready learned something, to go
back and refresh yourself, asopposed to like learning it the
first time, because I feel maybethere's a certain level of
anxiousness or anxiety around.
I don't know, I don't know whatI'm doing, I don't know if I
can get this done versus oh, Idid that a year ago, oh, okay.
(11:27):
Well, it looks like they've hada new update, so this button
has moved from this side of thepanel to this side of the panel.
You know, I mean, that's adifferent type of a challenge
then.
Speaker 3 (11:36):
And would you say that a lot of analytics jobs are
heavily using Power BI andTableau?
Like, from what I have heard,you can get an analyst position
and just be pushing outdashboards all day.
Essentially, it's still like asuper.
Yeah, it's a very in-demandskill to have.
(11:56):
Yeah.
Speaker 1 (11:59):
Yes, I feel like there are jobs where that's like
you are a Power BI developerand that's the main thing that
you do.
But you know there's a there'sa whole gambit of jobs, kind of
within the analytics Space.
You know cuz like financialanalysts are probably not doing
that.
Like the CFO of whatevercompany they're working for is
(12:21):
probably he's probably 30, 40years into his career.
He's been working with Excelfrom day one.
So like that is what they're,that's the tech stack they're
using.
That's like just kind of what'sbeen established there's so
much to Excel too.
Speaker 3 (12:38):
Yeah, it's crazy.
I feel like I learn new thingsto do in Excel just by scrolling
on Instagram or something.
Speaker 1 (12:46):
Yeah, well, it's interesting because Excel gets a
bad rap.
But it's like if you were agood problem solver and you have
some business domain, you cangenerate millions of dollars
worth of value from the workthat you do.
It's kind of weird to thinkabout.
It's like why do some of theseanalysts make so much money?
(13:08):
Well, it's like they, if theydidn't weren't in that role or
their role didn't exist, maybethe company would be a million
dollars less profitable.
Speaker 3 (13:19):
You know like you can't measure what you don't
track.
Speaker 1 (13:22):
Yeah, that's true.
Well, and then also.
But I feel like a lot ofanalysts get hyper fixated on
the technical stuff and maybeI'm falling into that with my
kind of worry around.
Like you know, I'm eight yearsinto working in analytics and I
haven't really gotten deep intoSQL.
Gotten deep into SQL.
Speaker 3 (13:42):
The thing about SQL also is it's kind of like Excel,
where there's so much that youcan do with it.
And I found myself to be thisway too when I first started
learning to query, where I kindof thought, oh, I've got my
(14:03):
select order by statement, I gotit, I got it.
And then now in my role, nowthere's uh, we use sql server as
our data warehouse, essentially, and it's so much to it, and
sometimes I'll just go readthrough the code for fun, trying
to understand it yeah but likeit's, you know I'm not writing
(14:23):
any sort of stored procedures oranything like that, you know.
Speaker 1 (14:27):
Okay.
Speaker 3 (14:28):
I feel like that's where your SQL skills get super
advanced.
I feel confident.
Like you said, you think that Icould learn relearn Tableau or
something within an hour.
I could teach you to write toquery data just as quickly, okay
.
And then you could go into yourjob.
Speaker 1 (14:46):
Well, I mean, I guess kind of where this thought is
is.
You know, right now I'm workingfor a pretty large company.
Back nine months ago, when Iwas interviewing you know, I had
three potential jobs that Iwanted to get.
One of them was the firstanalyst for, you know, I think
it was like a nine-figurebusiness, so like $150 million
(15:09):
to $150 million in revenue.
And the thing that knocked meout of the interview, they asked
me have you ever done a storedprocedure?
And I didn't even know whatthat meant.
I was like so humiliatedbecause I was like power bi
tableau the insights.
But there's a whole piece thatI'm missing from, like the data
(15:30):
engineering side to where, likeif, if I wanted to be the person
that ran the analytics for asmaller company, you, you can't
just have like that laserfocused right I am a sql
developer, BI developer or afinancial analyst that focuses
on this very specific.
Speaker 3 (15:48):
And I think that's the line between analyst and
developer as well, too.
Okay.
What does that mean?
A developer is really the personthat's doing the back-end
coding, the behind-the-scenessort of thing, where analyst.
I feel like it's going to saybad when I say it, but I want to
say it's almost the moresuperficial level.
(16:08):
You are taking what's alreadydone in the back end and you're
querying through that.
You're drawing insights.
Like whenever I'm querying data, you know I'm doing some tech
support.
There's an issue.
I can look into the data andfigure out what's missing, what
looks off.
Speaker 1 (16:28):
I'm going to yes and you.
Yes, from a tech standpoint,analysts have a superficial
understanding of what developersdo, but, on the flip side,
developers have a superficialunderstanding of the data
because they're not actually init.
You know they're not looking at.
Hey, here's our pricingstrategy.
(16:49):
Oh, you know, at this higherprice point, we sell X amount
lower.
No, they're working on like theactual kind of infrastructure
around that.
Yeah, yeah, that's a good point, yeah.
So it's like it's really likekind of pick your poison, and
I'm kind of leaning towards likemaybe I want to be in a
position where, like I'm almostlike a full stack developer I
(17:10):
don't know, I mean, it could besix months from now and it's
like, yeah, that idea was not atall what I thought I wanted to
pursue, or whatever.
Speaker 3 (17:18):
Well, I feel you on that because I'd say that was my
biggest motivation to get myMBA too.
Feel you on that because I'dsay that was my biggest
motivation to get my MBA too.
Is I wanted to be that bridgebetween tech and business acumen
, where am I going to be a fullstack developer probably not
ever, but I can try.
I've taken a course to startlearning like basic Java CSS,
(17:40):
java CSS, start using Git alittle bit, and that's just
surface level.
And then I know nothing aboutbusiness acumen.
I'm taking my I guess you couldsay second and a half course in
my MBA and I took my firstmarketing class and thought this
(18:01):
is everything.
I'm ready to go.
What's the point of the rest ofthese classes?
I've got this.
I learned so much.
Speaker 1 (18:08):
Now I'm in supply chains and I'm thinking yeah oh,
there's this I do, and well,and it's funny because, like I'm
, I'm kind of curious what youmean when you say business
acumen, because I am going tosay something that may come off
as controversial.
I'm not sure you can like learntrue business acumen in a
classroom.
Speaker 3 (18:27):
Interesting Okay.
Speaker 1 (18:29):
Like you can learn the fundamentals of marketing,
like, hey, here's a marketingfunnel, the top of the funnel is
awareness, and then there'snurturing, and then there's,
like the, you know sales yeah,unpack that a little bit, but
like it's one thingunderstanding like here is the
framework, but then going andapplying that framework out in
the real world.
That's when you're starting todeal with like ambiguity,
(18:51):
complexity.
You have to make assumptions,um, and I think that's I mean a
marketing class is a good startright maybe I don't know.
Speaker 3 (19:01):
There's so many very successful people that never
went to college.
Speaker 1 (19:09):
Yeah, well, I guess that's kind of what I'm.
A lot even that don't have anMBA.
Yeah, that's kind of what I'mgetting to is like there are
different courses or trains ofthought.
You could go and study what youwant to go or, you know, if
it's available available to you,you could go and get like a
marketing specialist job andwork and, you know, spend the
same two years.
(19:29):
You know, maybe we split thetimeline one year, one timeline
you're getting your MBA, theother one you're working as a
marketing specialist.
Speaker 3 (19:39):
Um, who knows, like so if you were not to get your
nba so you know nothing aboutbusiness, you know would the
only way to learn both sideswould be to get two different
jobs what do you mean by that?
Speaker 1 (19:54):
um, like you're saying that, no, well, okay,
well, I guess what I'm saying isthat college gives you like a
very theoretical, almost likesterile.
You know it's like we'relooking at this in a vacuum.
It's like the whole foundationsof economic theory, of well,
(20:17):
assuming that everything staysequal, which is like well, that
first assumption, if you raisetariffs, that's going to affect
other things in the economy.
Prices of goods are going to goup to the end consumer, which
is then going to Like there's,you're looking at that macro
level.
It gives you a perspective onkind of you know, broadly
(20:39):
speaking, how a business runs,but like you learn so much about
, like a very it's almost likean impeachment.
You're like dialed into onespecific aspect of the business.
Speaker 3 (20:50):
Yeah, so kind of the difference between understanding
and comprehending, where you,when you go to school, you
understand this material.
But until you're actually inthe workforce and using those
things that you learned andseeing how they intersect with
each other, that's where you geta comprehension of it.
Speaker 1 (21:09):
Well, okay.
So one thing you said before wehit record was you feel like
the MBA is a cheat code, and I'mnot trying to rain on your
parade by saying like you getlike a sterile kind of formal,
this is what.
But I will say the benefits ofan NBA is that you get a broader
perspective.
(21:30):
Yeah, because that person whowent and got the marketing
specialist just knows marketing.
Yeah, versus, like you'rezoomed out and you can.
You can kind of see like ohwell, you know we're marketing
really heavy for these areas,but we're having a supply chain
issue here.
So like it doesn't matter, ifthe marketing is effective in
(21:50):
florida, we can't ship anythingthere, it's just all going to
waste.
So like that's yeah it's kind ofa different game that you're
playing.
It's like almost you're gettinginto the world of strategy
versus in a marketing specialistrole.
You would be the executor, youwould be kind of running it and
then which I mean it?
You know we've talked for awhile.
Your goal is you want to moveinto management, right?
Speaker 3 (22:13):
yeah.
So when I said cheat code, whatI mean is I'm an analyst.
Now If you look at our orgchart, there are 20 people above
me, right, there is nobodybelow me.
How do I scale my career, right?
Do I just work as an analystand either job hop to eventually
(22:38):
get to a better position, or doI stay in my analyst role and
just, you know, grind it out andhope I get the promotions over
time and time and time and thenin 20 years I'm in a leadership
role where I can be an analystnow, get my MBA and then hope
(22:59):
that scales my career a littlebit, where maybe I can you know,
I don't know cut a couple stepsthere.
Or my next if I were to leavemy company, I would be able to
jump in at a higher role, right?
Yeah, who knows?
Speaker 1 (23:18):
This kind of circles back around to like.
One of the first things I saidwhen I was like opening the
podcast is there is an importantaspect that is neglected by
like I don't know 95 of peopleworking in analytics is building
relationships in the industry,and I will say an mba, a good
mba, so like, and I'm not evenwhen I it's funny when
(23:40):
university yeah when I say agood mba, I'm not even talking
about academics rightfunctionally speaking, a good
mba gets you plugged into anetwork and gets you because you
went.
Speaker 3 (23:52):
Yeah, I mean that's why I chose hp.
Speaker 1 (23:54):
Yeah hp is like very razzle-dazzle.
Speaker 3 (23:56):
Yeah, la-di-da.
Speaker 1 (23:57):
But I mean they have.
Devin Summers, who was in myclassroom here at Greensboro
College four years ago, wentdirectly from studying business
at Greensboro College gettingthe analytics minder, then
jumped directly into an MBA atHPU and then he got a senior
(24:18):
analyst role at NASCAR first jobout of the gate.
Speaker 3 (24:21):
That's awesome.
But the thing is like there's alot of stories like that too.
Right.
You know, I was razzle-dazzled abit whenever I did my tour of
HPU and instead of giving you apamphlet, they actually give you
these hardback books and theyhave all these, you know,
student success stories in theretoo, where their students are
(24:42):
getting internships, and that,ultimately, is what sold me,
because I could just go get apiece of paper and that's
probably not going to do for mewhat HPU would, where you would
get plugged into a network andget to meet people yeah, well, I
mean, I'm actually on theadvisory board for hpu's
(25:04):
business school.
Speaker 1 (25:05):
They have a whole like catalog of contacts of
former students and also peoplewho are like volunteering to
like work with hpu students andyou just go onto the Excel file.
It's got their telephone number, their email address, their
LinkedIn, so you can just go andreach out to them and connect
with them, which is I don't knowwhy all colleges and
(25:27):
universities are not doingsomething similar to that, but
that's hugely valuable becausethere's a whole hidden job
market out there where peopleare getting jobs because they're
not.
They're not even applying, it'sjust because, oh, the former
head of this department knowsthis.
This guy who works in analytics, he completely bypassed the
(25:51):
cold application process and gotdirectly to a you-round
interview because this personkind of vouched for him.
And you've got to bear in mindthere's dynamics at play with
that.
If that VP referred me to thejob and I had a bad job, that
would make him look bad, yeahabsolutely, and it would kind of
(26:13):
hurt his social capital, soreferrals are extremely valuable
.
Speaker 3 (26:20):
They are and I've ultimately a referral helped me
get my job now and it's I canconfidently say the position
that I'm in now is the first onethat I have where I really like
my job.
Speaker 1 (26:34):
Okay, that's a perfect conversation.
What does that mean?
Like what, and you don't haveto get into like this.
I don't want you to like throwanybody on their bus, but what's
a good job, what's a bad job,or what aspects make it good or
bad to you?
Speaker 3 (26:50):
Okay, Well, what I like about my job now is I love
my team.
I love the team that I workwith.
We help each other out.
There's no stupid questions.
There's a lot of like knowledgetransferring sessions.
Like hey, you want to learnthis?
Like let's hop on a call andwalk through this.
Or you have a question aboutthis?
Like let's get together andtalk about it.
(27:13):
I love that aspect of teamworkand team building.
I've seen growth in my rolewhere I haven't seen growth in
other positions.
Speaker 1 (27:25):
So it felt just like static, like there was no that.
I can see that as being verydemotivating of like absolutely
there's no room for growth here,so I'm just going to put in the
bare minimum, because I'm justwaiting for the next thing yeah.
Speaker 3 (27:38):
Yeah, yeah.
So there's that.
There's a lot of cross training.
I love being hybrid.
Yeah.
Where my office is.
It's like 10, 15 minutes away.
I go in about once a week andwe actually play Dungeons and
Dragons on our lunch break onWednesdays, which I absolutely
(27:58):
love.
So there's such a great culture.
It's a good snack If I need tostep out and run an important
errand you know nobody's goingto be like.
Did you put in your time forthose two hours while you were
doing this?
Or I called you and you didn'tanswer you're not micromanaged.
(28:19):
I'm not micromanaged.
I feel like an adult, yeahthere.
Speaker 1 (28:25):
I think there's also an aspect, too, of finding the
right kind of work as well.
Um so, do you enjoy the workitself?
Speaker 3 (28:34):
I really do, I really do so, I work in real estate
technology.
Speaker 1 (28:38):
You're like lighting up, talking about work.
Speaker 3 (28:41):
I know, isn't that funny.
Speaker 1 (28:42):
Yeah, that's awesome.
Speaker 3 (28:43):
I love it.
I work in real estatetechnology and I feel like in a
past life maybe I was a realtoror an interior designer or
something so I really enjoy thedata that I work with.
I think that makes a bigdifference too, because when I
worked at a CPA firm, it wasjust numbers.
Speaker 1 (29:01):
Accountants are some of the most flavorful, colorful
people I've ever met.
Sorry if you're an accountant,I'm not trying to like poo-poo
on you guys.
Speaker 3 (29:15):
What makes where I have been unhappy, what makes a
job not desirable, I would saywould be it was such a
high-stress work environmentwhere it was every single day.
We had a deadline to meet byfive o'clock but we couldn't
start.
You know pushing the data to gowhere it needed to go until
(29:35):
like 3.30.
Speaker 1 (29:37):
So you had like an hour and a half to get the thing
done.
Speaker 3 (29:39):
Yeah, if there was an error which errors happen all
the time it's like, okay, well,now you're working until 8 pm
every single day and my workschedule was like I was my
busiest from 3 pm until 8 pm.
Every day is what it felt like,and I was also super busy in
the morning.
So I'm still starting at 7.30,8 o'clock in the morning.
(30:00):
Oh wow, and it was just theselong days.
It felt like thankless work, tobe honest.
Okay, and a culture ofhostility where everybody was
just frantic.
I will quote this one thingthat someone said to me one time
.
Speaker 5 (30:19):
It's comical, it's in a call and they said I feel
like there is a train coming andI am standing on the track and
I know it's not going to stopand I'm just hoping that me
standing there will slow it downand ultimately I am going to
(30:40):
get run over and started tearingup, wow, and this was like a
senior level person and I waslike, yeah, this is awful,
because I feel.
Speaker 3 (30:52):
I mean, I don't feel like that, but I felt very
stressed and that's I rememberthe day I quit, or like my last
day there.
I didn't just quit, but I sleptall night, yeah, and I forgot
that I could do that yeah, Imean that's.
Speaker 1 (31:11):
That's a whole other aspect of like keeping an eye on
your mental health, like ifyou're not sleeping through the
night because you're so stressedabout work, that's beige,
probably a red flag.
Yeah.
Like I don't know.
I mean, maybe there's othercircumstances that are kind of
complicating things, but yeah,I'd say it's a red flag for sure
.
Yeah.
Speaker 3 (31:30):
I wouldn't say because you dream about work.
That's a red flag.
Like I, sometimes I dream thatI'm working now and it's still
stressful yeah like, especiallyif I'm kind of in the middle of
a problem that I'm working on,or like a project that is time
sensitive.
You know I'm thinking about it,but uh, it's definitely well, I
(31:51):
mean it's, it's sound.
Speaker 1 (31:53):
The assumption I'm making about that role that you
were in in the past is thatwhat's the saying?
Shit rolls downhill.
It sounds like.
Speaker 3 (32:01):
I have never heard that, but I would assume it does
.
Speaker 1 (32:05):
It sounds like the CEO might be under pressure from
the board and there might besome weird political stuff going
on, like maybe there's acorporate takeover and like
these people are trying to clingto like their job, and then
they put pressure on theirdirect reports and then their
direct reports get pressed andit's yeah, so we?
Speaker 3 (32:23):
what I was doing was covid rental relief
disbursements.
I think ultimately it wouldhave been a temporary position,
any like there's a lifetime tothat role, um, but you know,
banks close at five o'clock soyou get in everything you can
until the end of the day.
So really that's just how thesystem worked.
I don't know if there's abetter way around.
(32:44):
That.
That's above my pay grade, Iguess.
Speaker 1 (32:48):
It's something I don't like to say.
Yeah, but I mean you're gettingan MBA so soon to be not right?
Speaker 3 (32:52):
Right.
Speaker 1 (33:00):
I'm ready to take on anything now with my pay grade
just so I can learn more.
All right, so what classes areyou taking?
Speaker 3 (33:03):
I know you looked this up like right before I know
I said I should be able toanswer this.
Well, I finished on mymarketing based management class
.
I'm taking a supply chainoperations class and this is
what I looked up and I alreadyforgot what it was.
I think it's accountingfundamentals is the other course
(33:24):
, so that's like theprerequisite course and it's a
self-paced course.
So initially when I started myMBA, I wanted to do it full-time
so I could finish in a year andI thought a good way to test
the waters to see if I canmanage a full, if I could go
full-time, would be to.
I'm going to sign up for thisone class and then I have this
(33:45):
self-paced course at the sametime so I can finish that
whenever I want to.
I ultimately need that before Ican take other classes.
That did not work no.
I am could not handle theworkload of working full-time
and taking two MBA classes.
Yeah, it was too much.
(34:05):
It was too much, so I'm stillworking on that self-paced
course now alongside my supplychain class.
Speaker 1 (34:13):
So I mean this is a bit of a tangent, but how would
you rate your time managementskills out of 10?
Speaker 3 (34:20):
I would say if you asked me that question a few
months ago, I would say one ofmy weaknesses would be time
management.
But I think I've gotten to areally good place where I manage
my time really well.
I'm really good at blocking offmy calendar and my schedule
personal and work to make sure,like if something gets in yeah,
(34:42):
I can get it done, but what mybigness weakness is is based off
of that, and I don't even knowwhat you would call this is that
when something unexpected comesup now, that will sometimes
throw me into a frenzy.
Yeah, yeah, yeah.
Where I'm like, that willsometimes throw me into a frenzy
.
Yeah yeah, yeah, where I'm like.
Oh man, I didn't account forthis.
Right.
And now I have to, like I'vestacked up my time and yeah.
(35:06):
So I guess to mitigate that,like what I've done is I try to
get everything done Monday toFriday, so my weekends are my
weekends.
Yeah.
And if something comes up, thenI can.
Speaker 1 (35:16):
I mean you may also want to like bake in some safety
time.
Yeah.
Almost like an emergency fund.
You know like having a three tosix-month emergency fund makes
your finances so much lowerpressure.
Yeah.
But at the same time, though, ifyou're taking two classes and
you're working full-time and youhave a social life, yeah, I
mean, I don't know, my weekendshave become you're doing a lot
(35:45):
like right now it's you're.
You're getting used to beinglike very busy and I think that
that's stretching you in a goodway yeah, I hope so, I'd imagine
.
Speaker 3 (35:55):
I hear all these senior positions are working off
the wall hours.
So if I, if I'm filling up mytime with that many hours, then
if I could just do one thing forall of those hours, maybe that
would be easier.
Speaker 1 (36:12):
As you're moving kind of up a hierarchy, I think you
have to deal with broader setsof problems, or I mean and I
guess this is anotherconversation, living back to
what we were talking about withyou know, getting growing in
your career, like there are twopaths kind of within analytics,
so like you could move intomanagement, or you could become
(36:35):
like a highly specializedindividual contributor.
Yeah.
Where you're doing like I'mtrying to.
Speaker 3 (36:40):
I wouldn't mind that either, honestly.
Speaker 1 (36:43):
Which like, but I feel like being an individual
contributor might kind ofconflict with the nature of an
MBAba, because the nature of anmba is kind of wide, yeah versus
a getting a like a phd ingeospatial science, like what is
.
Isn't that what kinga has?
Geospatial she has like a phdin like environmental science,
like focusing on, like geographythat sounds she now is a data
(37:06):
scientist that works for a floodrisk startup.
Yeah.
I mean that's like think abouthow specialized that is, like
you've studied this forenvironmental stuff, for I don't
know.
Speaker 3 (37:17):
A PhD.
Oh my gosh.
I hear those can take two yearsto more.
Yeah, like do they take youfive.
Speaker 1 (37:26):
So that's like an area that she studied and she's
become an expert on and then sheconsults in that space, versus,
like, going the nba route.
Yeah, you might have to.
There are certain threads thatare going to span multiple kind
of verticals and departments,and higher up the organization
you go, the more you kind ofhave to to deal with that yeah,
(37:49):
yeah, absolutely so yeah, it's.
It's just, I think, you'rehaving to deal with like more
uncertainty as well, you knowwhich, and that, I think takes
the ability to kind ofself-soothe and deal with
anxiety, which sounds likeyou've also gotten better at
that too.
Speaker 3 (38:08):
Yeah, I would say so.
I think me going to the gym isa big part of that, and then,
unfortunately, with my schedule,now that's not something I'm
able to do like I was, butmaking sure that I get there at
least once a week it does help,for sure.
For sure.
Speaker 1 (38:28):
I got you.
Okay, once a week is it doeshelp.
Speaker 3 (38:30):
For sure, for sure, I got you, so okay, so you're a
semester in or two, technicallyyeah, so two mini masters in
which would or like the secondhalf of one mini master in the
first half of another, I mean.
Speaker 1 (38:42):
I'm just one.
I'm kind of curious, Like doyou have like a specific title
or direction that you want to goin?
Speaker 3 (38:58):
Because I feel like there are a lot of people who
have the same kind of instinctthat you have of like, oh, if I
get a master's degree, that'sgoing to open doors up for me.
Yeah, it's interesting.
I did this HPU MBA summit.
I met a lot of the otherstudents and I was very
impressed how many people knowexactly what they want to do and
I don't.
But I think I'm just going to.
I'm still trying to figure itout.
(39:20):
I know that I want to be abridge between.
I'm not the most technicalperson in the world.
Obviously, Like I said, I'm notgoing to be a full-stack
developer or anything, but I canbe more technical than most and
have that business acumen andbe able to be in a leadership
role where I can convey whatneeds to be conveyed and, you
(39:42):
know, do the thing.
I guess If I had a title inmind, I don't ever want to be a
CEO, but wouldn't it be cool ifI was like a CIO or, you know, a
CTO?
I don't know, Maybe I need tobe more technical than what I'm
imagining, but I'm still tryingto grow my technical skills.
In the position that I'm in now, I still have the opportunity
(40:04):
to learn a lot of new things andI am actively learning every
day on the job.
So I'm hoping, as that growsand then by the time.
I get my MBA.
Maybe there's also the impostersyndrome, like I don't know.
Probably won't ever be goodenough for that, but if I aim
for it, we'll see where I fall.
Speaker 1 (40:20):
You're cracking me up a little bit because you just
said I don't know what I want todo and then proceeded to give
me a very detailed breakdown ofwhat you want to do, so like I
don't know.
If that's fair.
Like well are the people thatyou're like that were in that
orientation, where they like Iwant to be at this specific
(40:40):
company at this pay.
Like that feels a little rigidto me.
Yeah.
It's like your, your kind ofvision for like where growth
could go or where your careergrowth could be, feels kind of
realistic, like it's not.
You know, I need to get a jobat Meta and that's success.
Yeah.
Because it's like you get inthere and then what you know
(41:00):
like that's yours, seems kind ofa little pliable A little bit
pliable.
Speaker 3 (41:06):
Which is just more realistic.
I would hope so.
Yeah, and I like working intech now and I would be
interested in other fields too.
Just hearing about the freshmarket honestly.
Yeah, first of all, that 40%discount.
Speaker 1 (41:22):
I don't know if I can say that on air, but that's
incentivizing, I mean, I guessthat's like free promo for them.
Speaker 3 (41:28):
Yeah, I have friends that do really well in retail
too, and I think that's superinteresting as well.
Personally, I love retail, I'ma shopper, I love Target.
Speaker 1 (41:43):
Okay, well, I mean, it sounds like you.
Speaker 3 (41:45):
I feel like I am very adapt, adaptable and I can find
happiness in a lot of places.
Um so, in the space that I'm innow, the the real estate.
It's not what I would have ever, it's not what I expected or
ever aimed for, but, right, it'scool.
I really like it, I really likeit um, I know what I don't like
.
I I don't want to work for afinancial institution.
(42:06):
I know I don't want to work forany.
I don't want to work for afinancial institution.
I know I don't want to work forany pharmaceutical company.
Never would want to work forthe government, like any sort of
government sector.
So yeah, I mean I have a littlebit of direction, like I know
enough to stay in a lane, butyou know I would be willing to
take multiple paths.
Speaker 1 (42:27):
Well, you have a lot to build off of.
You know a lot of experience,like a lot of skills and
knowledge, because I was talkingwith somebody I think it might
have been a student of how manypeople know Excel.
You know probably, like Idon't't know Excel at all
(42:48):
probably 95% of corporate people, but how many people know it
above a 5 out of 10?
Yeah, then that breaks it downto like I don't know 20% of
people but it's.
Speaker 3 (43:00):
I feel like that brings us into the conversation
of AI, because Excel I thinkit's Excel right, they have a
new AI assistant that you canuse, whereas, basically, if you
know the basics, if you knowwhat questions to ask, then you
can do anything which.
I feel like that was truebefore.
You just had to be willing todo your due diligence and
(43:21):
research to be like how do Icreate a dropdown menu?
Right now, you could just usethe the tool and it's going to
go ahead and make it for you, uh, but I wonder, does that raise
the bar?
You know if everybody can do nothat was another, um uh,
incentive for me to get my mbatoo, where like to set yourself
(43:44):
apart yeah, I don't know if Ican keep up with.
I don't know if I can keep upwith tech has?
Speaker 1 (43:52):
has daniel hall not told you his whole take on ai?
No, tell me um, ai is not goingto replace your job, it's just
going to augment it yeah, butmore people are going to be able
to do that job.
Speaker 3 (44:02):
Now, that's what I think um and empower more people
to be able to do.
Speaker 1 (44:07):
I think you are undervaluing the fact that you
have a five-year-long history ofworking with data, the critical
thinking ability that youdeveloped, and like the
intuition and asking the rightquestions, you know, like
because, yeah, the new thing isgoing to be prompt engineering.
But the fact that you've workedwith data and you're like, oh,
(44:30):
this data looks wrong, so it'slike, okay, why might this data
be wrong?
Oh, it's because this table'snot joined correctly, so you can
go and follow the thread,versus, like, some average
person might not even be able torecognize mistakes.
They're just going to ask hey,you know why were sales down
(44:50):
last week?
And then it would give like asee, I'm not so sure that like
AI, is this super pill?
Like there's so manyassumptions and there's so much
like gray, that like.
Speaker 3 (45:04):
I feel like it's going to change.
It is already changing a lot ofthings.
Speaker 1 (45:06):
It will change the nature of work.
Speaker 3 (45:08):
yeah, For example, in my role as a data scientist,
one of the last things I wasworking on with my team was
creating a new API connection tothis new platform we were using
In my role.
Now I wanted to connect to anAPI to pull specific data.
(45:28):
I went to chat GBT Obviously Idon't use this on my work
computer, but I'll use it on myregular computer and then, you
know, copy the script over.
But I went to chat GBT saidconnect me to this API, I want
to pull this, this and this, andthen I am able to just set up
my connections with mycredentials and the data's there
(45:52):
.
Where.
That took like my team beforewe were working on creating this
API connection for like a monthor two and it took me 15
minutes.
Speaker 1 (46:03):
That's crazy, yeah.
To do it now, Well, that's ahuge amount of leverage.
15 minutes that's crazy.
Yeah, Do it now Well, that's ahuge amount of leverage.
But the problem with leverageis it can go both ways right.
Like if I'm buying a short forthe housing market in 2007,
that's awesome.
But if I were, you know, if Ileveraged some cash to go and
buy a house in 2007, I would beout, I don't know, probably a
(46:28):
few hundred thousand dollars.
So, like AI can be really good,it also can be there's a
liability or a risk to it.
Yeah.
Speaker 3 (46:35):
Because if you're just going off of what it's
telling you without fullyunderstanding, like, hey, this
checks out, this makes sense,and like understanding the use
case and the contributingfactors to why you know things
might be this way or that way,yeah, um so I guess how you were
saying I was underplayingmyself before, like I think I do
still like believe that it'strue that more people are going
(46:56):
to be able to do those likebasic to intermediary yeah, or
intermediate skill level taskslike with an Excel or BI
assistance, tableau assistance,whatever.
But I think also there's thatscalable too.
So if you're at a level three,maybe you can jump to a level
(47:18):
five where you wouldn't be ableto before.
So maybe I should look at it atthat perspective instead of
like oh no, I'm a level three,everybody's about to be a level
three.
Speaker 1 (47:31):
You know what I'm saying.
Yeah, I think you'redownplaying yourself.
I think it might be someimposter syndrome um, I don't
know that's.
I think you're in a great spot.
You know, like you've you'vegot five years of experience is
very, very important or very keyright now.
Yeah, because it's, it's veryhard to break into analytics
(47:51):
right now.
Is it?
It's, it's gotten.
I mean, I shut down my careerservices program cause I, you
know, I had a hundred percentmoney back guarantee and it was
like same program, samemethodology.
You know, about a year ago Iguess, like, oh, like, maybe a
year and a half, two years ago,at this point the job market,
(48:11):
especially for entry level, justkind of tanked.
Speaker 3 (48:15):
And you know what I have found is being an analyst.
I still do believe that it'slike a commendable title.
However, I feel like it'sbecome like it's getting diluted
right.
Speaker 1 (48:26):
Yes, it's become this diluted right.
Speaker 3 (48:27):
Yes, it's become this buzzword essentially.
I know, uh like my company dida restructure of positions and
now it's like everybody's ananalyst.
Speaker 1 (48:38):
Yeah.
Speaker 3 (48:39):
Everybody's an analyst Well and.
I see that, and just looking atother jobs online too, uh like
there's a financial analyst.
I'm reading what's required andit sounds like a typical
analytics job.
And then I go to the next oneand it has nothing to do with
analytics.
Speaker 1 (48:56):
Yeah.
Speaker 3 (48:58):
And.
Speaker 1 (49:00):
There is some kind of like, but at the same time
titles are somewhat arbitrary.
Like for, for example, youmentioned, like the banking
industry, apparently it's likenot that hard to become a vp,
like a like, yeah, like, becauseI I think that, or maybe I
shouldn't say it's not that hard.
But a vp at the fresh market isyou're one level below c-suite,
(49:23):
but a vp within like I don'tknow, truest, for example, I
think there's like multiplebusiness units.
A vp is like a manager or adirector level, maybe more
accurate to be a director level,because then there's like
senior vps and then there's likeI don't know so that also gets
you back to like what size isyour company essentially?
Speaker 3 (49:44):
too yeah like there's a lot of intermediate, there's
those small companies, there'smeta, and then there's so many
in between where I don't think Iwork for a huge company per se,
definitely not like meta.
Yeah.
But there's still at least 10people above me.
Speaker 1 (50:05):
That's crazy.
I'm trying to think about, like, in my current position, how
many people are above me.
I think there's only like two,three levels of management above
me, maybe two look at you, bigshot well, but it's a different
I.
I think it's a flatterorganization maybe, and that's
see that that we could go onit's.
It's an endless conversationaround, like you know what's the
(50:27):
size of your company, whatindustry are you in, what
vertical within that industry.
So yeah, but I guess I'llcaveat this of like, if you're
getting a new job, they don'texpect you to know everything,
but if you have like a history,if you have five years of
working with data, variousdifferent companies, various
(50:47):
different industries, that givesyou a starting point, that
gives you a leg up over, youknow, people who are just
starting out, entry level, thathave access to AI.
I feel like you're downplayingthat.
I'm trying to like pump you upa little bit, but you've got
this body of work, theseexperiences, these skills and
(51:09):
these wins, quite frankly, thatare kind of mental models in
your head that you can use tonavigate.
Speaker 3 (51:15):
Yeah, yeah, I mean, ai is definitely here to stay.
So I think that's somethingthat everybody's going to be
using, and even my husband'scompany.
They have an internal AI fortheir whole organization and
it's been incredibly useful tojust say, like go in and you can
ask, right that's crazy overthis project and it will pull up
(51:37):
this.
Or, like you can ask questionswhere you might spend time, you
know, going through the officeor he works in manufacturing, so
going from this person to thisperson to this person to try to
figure out an answer where youcan use the AI now and that's
not enhancing anybody's job aslike as a skill set, essentially
(52:00):
, but it is enhancing your job,the time you would spend doing
certain things and increasingaccuracy.
Right.
Reducing bottlenecks.
I guess you could say wherelike people might get stuck and
be going to the wrong person.
For this one thing, thisproject is getting delayed or
not.
All the information is thereand now this ai tool is there to
(52:21):
like, let the data flow orsomething.
Speaker 1 (52:27):
Yeah, I feel like AI is where analytics was.
When you and I first sat downat Mythos on Market Street in
Greensboro the beginning andlooked at Because I mean, I feel
like you got into the analyticsmarket at a really good time.
Speaker 3 (52:42):
I think so too, you know like Because I remember I
was really wanting that analystposition and I didn't get an
analyst position right away yeah, a data mining position.
But I thought, okay, well, thisis good I.
Speaker 1 (52:55):
I took a data mining class in my gis course in
college, so I was like you knowright, but I mean, even that is
like enough of an end to likelook, look, what you've done.
Speaker 3 (53:06):
It's working with data.
Yeah, you know like it'sworking with big data.
Right.
It's such a valuable thing,it's such a transferable skill.
Speaker 1 (53:16):
I gotcha All right.
Well, let's wrap this bad boyup.
Do you have any closingthoughts on how people can get
an analytics job?
Speaker 3 (53:25):
Craig's sitting right here off screen what do you
have to say to Craig Just beopen, you know.
Yeah.
Like if there is one thing thatyou know that you want to do,
definitely go for it, but don'tbe afraid to take a baby step
first and then jump from thereLike just get in.
Speaker 6 (53:48):
Yeah, yeah, I definitely.
That's kind of the advice thatI'm hearing from a lot of my
professors nowadays is, ifyou're a really smart person, if
you have critical thinkingskills you know there's not a
good way to show that on yourresume and your application, but
if you just get in, if you'rean impressive person, you will
impress somebody.
Speaker 1 (54:12):
And you just have to get that personal, you just get
in you know if you're animpressive person.
You will impress somebody andyou just have to get that
personal.
You just have to get in.
Well, good luck on yourinterview on monday.
Thank you, I mean craig's anoverachiever, if you do, you
mind me.
Yeah, we can talk about that,all right.
So you got an interview for uh,is it like essentially like a
project management?
Speaker 6 (54:24):
uh, it's a it's a project management position at
an architectural design company,but the deal is kind of it's a
growing position and so if aproject manager like this will
be the first time they hiredsomebody to do that, so that
person also needs to know someanalytics.
They need to know we're gettingall these new numbers.
It's the first time thecompany's had all these numbers.
(54:44):
Somebody needs to know what todo with all these numbers,
because that's like a freshthing to them.
Speaker 1 (54:50):
Well, you said you read a book on architecture in
the last two days.
Speaker 6 (54:54):
Yeah, well, I've been studying up, so I went to Books
A Million and got a copy of abook on the architectural
business.
Speaker 1 (55:02):
It was like 200 pages .
Speaker 6 (55:03):
It wasn't architecture for dummies.
No, I didn't pick uparchitecture for dummies.
There was project managementfor dummies.
Yeah, you sent me some picturesof that.
That was funny, but I don'tknow.
I've actually read some of thefor dummies books and they're
kind of like for dummies, youknow.
Speaker 3 (55:18):
It helped me pass chemistry.
I will say that I've got achemistry for dummies alongside
my textbook Gotcha for dummiesalongside my textbook Gotcha I'm
a dummy there.
Speaker 1 (55:28):
All right.
Well, molly.
Thank you so much for your time.
Craig, good luck on Monday.
I know you're going to kill it.
And thank you all for tuning into the episode.
Speaker 3 (55:36):
Thanks for having me.
Hello and welcome back to the how to Get an
Analytics Job podcast.
So today we're going to betalking about the importance of
building industry friends andthe amount of opportunities that
can bring you.
I'm also going to be talking tomy guest about SQL what you
need to know, what's the bestway to learn it and how does it
show up in a day-to-dayworkforce.
(00:31):
And then also she is going andgetting an MBA to advance her
analytics career.
So our guest is Molly, who,coincidentally, is actually the
first person back.
What was it five years ago?
Yeah?
Five years ago, five years agoGetting getting.
I helped you get your firstanalytics job.
Um.
So I know some of the guestshave probably you've been on
(00:57):
quite a few times over the yearsyeah, there was an episode with
Gary Fly.
Speaker 3 (01:01):
Yeah, um, and I'm not sure if that was my only
episode or not, but I doremember that one specifically.
Speaker 1 (01:07):
Yeah, well, I feel like you've been on In the chats
heavily.
Yeah.
Speaker 3 (01:11):
Yeah, the YouTube chats.
Speaker 1 (01:13):
Yeah, yeah.
Well, you're a great kind ofresource that I can like.
I want people like you becauseI mean, you can't see it, but we
got a Greensboro Collegestudent kind of running behind
the scenes, craig, over there.
Craig's killing it.
Just like having someone that'sfive years into their career
interacting with someone who'slooking to get their foot in the
door.
Like you were saying off airthat you were a little bit
(01:36):
nervous, but like just givingyour authentic opinion about you
know what's been yourexperience is hugely insightful
for someone like Craig.
Speaker 3 (01:46):
Yeah, I mean I really , I would just say jump into it.
Speaker 1 (01:51):
Yeah.
Speaker 3 (01:51):
You know, especially your first job, I wouldn't worry
too hard about is this theperfect fit or not, because
ultimately you're not going toknow until you start gaining
some of that experience.
Like you know, what is it thatyou're looking for in a position
.
What kind of management styledo you prefer?
What kind of workflow style?
Speaker 1 (02:09):
do you prefer what size company?
Speaker 3 (02:10):
What size company?
Speaker 1 (02:11):
You know like there's pros and cons.
If you're working in a hugecompany, you're a cog on a very
large wheel, but if you're in asmall company, you might be the
only person who knows analyticsin the entire company yeah, only
(02:31):
person who knows analytics inthe entire company.
So, and there's a lot ofin-between ground there too,
right?
Well, I mean, I guess let meask you this have you worked?
It sounds like well.
How many jobs have you had in?
Speaker 3 (02:35):
analytics over the last five years is it?
Is it two or three?
My third yeah okay, so my firsttwo were uh jumps, and they
were all so different from eachother, right?
Speaker 1 (02:43):
what, but that's like I feel like that's great advice
, though, because the first jobyou got you, I think you
probably you didn't like it, foryou don't have to be explicit,
but like X, y, z, reason.
Speaker 3 (02:54):
Yeah, so I enjoyed it .
I was working agrochemicalsfirst and doing data mining and
it was a very generous title.
I definitely learned a lot, butthere wasn't any sort of like.
I wasn't using any sort of SQL,I was using Microsoft Excel.
That's it.
Speaker 1 (03:11):
Right.
Speaker 3 (03:12):
And I got pretty good with Excel and automating
things within Excel and then Imade a big leap to.
So I stayed there for a yearand after a year I made a big
leap to a CPA firm as a datascientist, where I just was
diving right into APIs usingPython.
Speaker 1 (03:36):
Well, I guess, let me from a third-party perspective.
I remember you during that timeand you were so stressed.
I was so stressed.
So, like I hear the advice of,like you want to jump in with
both feet, there are downsidesto that approach.
Yeah, because, like you weregoing from like Excel to Python,
(03:57):
I mean from like data miner todata scientist.
Yeah, which, like I mean, kudosto you.
Speaker 3 (04:07):
I mean you like you.
Speaker 1 (04:08):
You like stuck it out and like got on top of it.
Yeah, um, because it soundslike the well.
I mean, I remember talking toyou during that time and you
were like just it was likedrinking water out of a fire
hose.
Speaker 3 (04:22):
However, I will say and I do think that this is
important, regardless of whatfield you're going into and what
type of position is just reallybeing honest about what you are
capable of.
So I had just done I think itwas like a data boot camp online
(04:42):
and did like a eBay webscraping project that I didn't
even know was technically it'snot illegal, but like you're not
supposed to do that, right?
And I was like yeah, this iswhat I can do and I'm using
Python's like or Python, thepandas library.
So I was like okay, I can, Ican clean data and kind of went
into my interview just beinghonest about that and trying to
(05:08):
be as confident as I can.
So they knew where I was at,but they were ready to be like
cool, you know how to run somecode, let's throw you into the
deep end.
But I did have a really greatboss and a lot of guidance there
, and I think it was a learningexperience that I wouldn't have
been able to teach myself on myown.
Speaker 1 (05:29):
Right.
Well, I mean, if you thinkabout it, like the
accountability there, you eitherfigure this out or you get
fired.
You know that it's a little bitmore than like oh, I found a
free YouTube resource, likethat's the accountability
there's kind of tough.
I mean, I guess you can pay forcontent or you could sign up
for like a you know college orboot camp, and like, having that
(05:50):
money on the line of like I'mpaying for this, if I don't get
it done, if I don't finish it,I'm just wasting my time and my
money.
Yeah, but you did it on likesuper hard mode.
It's like I'm going to lose myjob and my income, which I mean
that is kind of a cheat code.
(06:11):
What were you going to say?
Speaker 3 (06:12):
Well, I was going to say, to be fair, I jumped into
this position that felt veryadvanced from where I was coming
from, for sure, but I was morelike running the code and making
tweaks to it and then editing,like when the code would fail
I'd have to troubleshoot it,which was still very difficult,
(06:34):
as opposed to like I didn't getthe job and then they expected
me to write this elaborate code.
Speaker 1 (06:40):
Gotcha.
Speaker 3 (06:43):
At some point I had to do that.
That was stressful.
Speaker 1 (06:51):
It's funny because I kind of feel the same way or
similarly about SQL.
I think I built it up in myhead a little bit I don't want
to do SQL, I don't really likecoding.
But I'm realizing now because Ihave recruiters approaching me
fairly regularly and one of thequestions that keeps coming up
and up is do you have SQLknowledge?
(07:11):
And I guess, before we get intothe topic, I want to kind of
elaborate.
You can be an analyst and workin Excel.
Like financial analysts, Ithink pretty much across the
board, unless you're at like avery high level, are mostly in
Excel.
Like financial analysts, Ithink, pretty much across the
board, unless you're at like avery high level, are mostly
using Excel.
Speaker 3 (07:29):
Anything I do in SQL or Python ends up getting
exported to Excel anyway.
Speaker 1 (07:36):
So you don't have to learn SQL.
I feel like that's likesacrilege.
Like you know, you go onLinkedIn and everyone's posting
about SQL, blah, blah, blah,blah.
It's not relevant for I wouldsay, like non-tech brick and
mortar, like you know, if youwork at a grocery store, they're
probably not having the peoplethat are actually digging
(07:58):
through the data.
Most of that heavy lift isgoing to be in Excel.
There are going to be likebusiness intelligence people,
people who kind of run thebehind the scenes, but it's
mostly like a self-service towhere you have a GUI.
For example, microstrategy isan example of that.
You sign into it and then it'sgot a list of folders and it's
like all right, I want stateattribute and I want sales, and
(08:21):
then you just click and drag itin there and then hit export and
then it's in Excel.
Speaker 3 (08:26):
Yeah, and so after my data scientist position, I'm
now a data analyst, so it's kindof a funny transition there.
But now I work at a techcompany and I would say it is
very it's funny.
I'm a data analyst, but I don'tdo analytics.
Speaker 1 (08:44):
What does that mean?
Speaker 3 (08:46):
well, when I think of analytics, I think about power
bi, I'm thinking about, like,pulling all of this data and
then creating insights from it,as opposed to now, where I am, I
do a lot of tech support, I doa lot of data mapping, um so
like etL.
Yeah, that's like yeah.
Speaker 1 (09:08):
Essentially.
Yeah, I mean that's so.
You're basically like creatingthe sandbox in which you know an
analyst who might even be usingExcel is coming in and like
knows the business?
So there's kind of that, thatspectrum of you know.
Do you sit more within thesystems side of things or are
you more kind of in the business, influencing decisions?
Speaker 3 (09:28):
Yes, and even to like be a data scientist or do
traditional analytics, I wouldagree with you that, like you,
probably don't have to use SQLif you don't need to be
accessing these large data setsyourself, if you can get
somebody to pull that data foryou you can do all the analytics
(09:51):
outside of it for sure,especially like Tableau Power BI
.
It's funny those are tools thatI use to put on my resume and
I've done the projects but, I,would be if I went for my next
interview and they asked me if Icould you know if I use Power
BI and Tableau.
I'd say I've used it before andI feel confident that I could
(10:13):
you know, it's like riding abike.
Speaker 1 (10:16):
Yeah, Well, I mean, BI tools are like.
Speaker 3 (10:18):
I don't know, it might take me a while.
Speaker 1 (10:20):
Well, I mean, it's kind of 80-20, right, like
there's in Power BI or Tableauor whatever.
I'm confident that if I gaveyou an hour, you could probably
connect to a data set, pull itin and build out a very simple
interactive dashboard Like it.
You know, maybe an hour is liketoo zealous.
Speaker 3 (10:43):
Maybe if I gave you a day, I did make a map at my
current position that ended upnot being used at all, but that
was kind of relearning it, whereI think I spent an hour at
least relearning how to do it.
But then, once the data was inthere, it took about 15 minutes
to make the map.
Speaker 1 (11:03):
Yeah, I was about to say it's more of a refresher.
It's so much easier, if you'vealready learned something, to go
back and refresh yourself, asopposed to like learning it the
first time, because I feel maybethere's a certain level of
anxiousness or anxiety around.
I don't know, I don't know whatI'm doing, I don't know if I
can get this done versus oh, Idid that a year ago, oh, okay.
(11:27):
Well, it looks like they've hada new update, so this button
has moved from this side of thepanel to this side of the panel.
You know, I mean, that's adifferent type of a challenge
then.
Speaker 3 (11:36):
And would you say that a lot of analytics jobs are
heavily using Power BI andTableau?
Like, from what I have heard,you can get an analyst position
and just be pushing outdashboards all day.
Essentially, it's still like asuper.
Yeah, it's a very in-demandskill to have.
(11:56):
Yeah.
Speaker 1 (11:59):
Yes, I feel like there are jobs where that's like
you are a Power BI developerand that's the main thing that
you do.
But you know there's a there'sa whole gambit of jobs, kind of
within the analytics Space.
You know cuz like financialanalysts are probably not doing
that.
Like the CFO of whatevercompany they're working for is
(12:21):
probably he's probably 30, 40years into his career.
He's been working with Excelfrom day one.
So like that is what they're,that's the tech stack they're
using.
That's like just kind of what'sbeen established there's so
much to Excel too.
Speaker 3 (12:38):
Yeah, it's crazy.
I feel like I learn new thingsto do in Excel just by scrolling
on Instagram or something.
Speaker 1 (12:46):
Yeah, well, it's interesting because Excel gets a
bad rap.
But it's like if you were agood problem solver and you have
some business domain, you cangenerate millions of dollars
worth of value from the workthat you do.
It's kind of weird to thinkabout.
It's like why do some of theseanalysts make so much money?
(13:08):
Well, it's like they, if theydidn't weren't in that role or
their role didn't exist, maybethe company would be a million
dollars less profitable.
Speaker 3 (13:19):
You know like you can't measure what you don't
track.
Speaker 1 (13:22):
Yeah, that's true.
Well, and then also.
But I feel like a lot ofanalysts get hyper fixated on
the technical stuff and maybeI'm falling into that with my
kind of worry around.
Like you know, I'm eight yearsinto working in analytics and I
haven't really gotten deep intoSQL.
Gotten deep into SQL.
Speaker 3 (13:42):
The thing about SQL also is it's kind of like Excel,
where there's so much that youcan do with it.
And I found myself to be thisway too when I first started
learning to query, where I kindof thought, oh, I've got my
(14:03):
select order by statement, I gotit, I got it.
And then now in my role, nowthere's uh, we use sql server as
our data warehouse, essentially, and it's so much to it, and
sometimes I'll just go readthrough the code for fun, trying
to understand it yeah but likeit's, you know I'm not writing
(14:23):
any sort of stored procedures oranything like that, you know.
Speaker 1 (14:27):
Okay.
Speaker 3 (14:28):
I feel like that's where your SQL skills get super
advanced.
I feel confident.
Like you said, you think that Icould learn relearn Tableau or
something within an hour.
I could teach you to write toquery data just as quickly, okay
.
And then you could go into yourjob.
Speaker 1 (14:46):
Well, I mean, I guess kind of where this thought is
is.
You know, right now I'm workingfor a pretty large company.
Back nine months ago, when Iwas interviewing you know, I had
three potential jobs that Iwanted to get.
One of them was the firstanalyst for, you know, I think
it was like a nine-figurebusiness, so like $150 million
(15:09):
to $150 million in revenue.
And the thing that knocked meout of the interview, they asked
me have you ever done a storedprocedure?
And I didn't even know whatthat meant.
I was like so humiliatedbecause I was like power bi
tableau the insights.
But there's a whole piece thatI'm missing from, like the data
(15:30):
engineering side to where, likeif, if I wanted to be the person
that ran the analytics for asmaller company, you, you can't
just have like that laserfocused right I am a sql
developer, BI developer or afinancial analyst that focuses
on this very specific.
Speaker 3 (15:48):
And I think that's the line between analyst and
developer as well, too.
Okay.
What does that mean?
A developer is really the personthat's doing the back-end
coding, the behind-the-scenessort of thing, where analyst.
I feel like it's going to saybad when I say it, but I want to
say it's almost the moresuperficial level.
(16:08):
You are taking what's alreadydone in the back end and you're
querying through that.
You're drawing insights.
Like whenever I'm querying data, you know I'm doing some tech
support.
There's an issue.
I can look into the data andfigure out what's missing, what
looks off.
Speaker 1 (16:28):
I'm going to yes and you.
Yes, from a tech standpoint,analysts have a superficial
understanding of what developersdo, but, on the flip side,
developers have a superficialunderstanding of the data
because they're not actually init.
You know they're not looking at.
Hey, here's our pricingstrategy.
(16:49):
Oh, you know, at this higherprice point, we sell X amount
lower.
No, they're working on like theactual kind of infrastructure
around that.
Yeah, yeah, that's a good point, yeah.
So it's like it's really likekind of pick your poison, and
I'm kind of leaning towards likemaybe I want to be in a
position where, like I'm almostlike a full stack developer I
(17:10):
don't know, I mean, it could besix months from now and it's
like, yeah, that idea was not atall what I thought I wanted to
pursue, or whatever.
Speaker 3 (17:18):
Well, I feel you on that because I'd say that was my
biggest motivation to get myMBA too.
Feel you on that because I'dsay that was my biggest
motivation to get my MBA too.
Is I wanted to be that bridgebetween tech and business acumen
, where am I going to be a fullstack developer probably not
ever, but I can try.
I've taken a course to startlearning like basic Java CSS,
(17:40):
java CSS, start using Git alittle bit, and that's just
surface level.
And then I know nothing aboutbusiness acumen.
I'm taking my I guess you couldsay second and a half course in
my MBA and I took my firstmarketing class and thought this
(18:01):
is everything.
I'm ready to go.
What's the point of the rest ofthese classes?
I've got this.
I learned so much.
Speaker 1 (18:08):
Now I'm in supply chains and I'm thinking yeah oh,
there's this I do, and well,and it's funny because, like I'm
, I'm kind of curious what youmean when you say business
acumen, because I am going tosay something that may come off
as controversial.
I'm not sure you can like learntrue business acumen in a
classroom.
Speaker 3 (18:27):
Interesting Okay.
Speaker 1 (18:29):
Like you can learn the fundamentals of marketing,
like, hey, here's a marketingfunnel, the top of the funnel is
awareness, and then there'snurturing, and then there's,
like the, you know sales yeah,unpack that a little bit, but
like it's one thingunderstanding like here is the
framework, but then going andapplying that framework out in
the real world.
That's when you're starting todeal with like ambiguity,
(18:51):
complexity.
You have to make assumptions,um, and I think that's I mean a
marketing class is a good startright maybe I don't know.
Speaker 3 (19:01):
There's so many very successful people that never
went to college.
Speaker 1 (19:09):
Yeah, well, I guess that's kind of what I'm.
A lot even that don't have anMBA.
Yeah, that's kind of what I'mgetting to is like there are
different courses or trains ofthought.
You could go and study what youwant to go or, you know, if
it's available available to you,you could go and get like a
marketing specialist job andwork and, you know, spend the
same two years.
(19:29):
You know, maybe we split thetimeline one year, one timeline
you're getting your MBA, theother one you're working as a
marketing specialist.
Speaker 3 (19:39):
Um, who knows, like so if you were not to get your
nba so you know nothing aboutbusiness, you know would the
only way to learn both sideswould be to get two different
jobs what do you mean by that?
Speaker 1 (19:54):
um, like you're saying that, no, well, okay,
well, I guess what I'm saying isthat college gives you like a
very theoretical, almost likesterile.
You know it's like we'relooking at this in a vacuum.
It's like the whole foundationsof economic theory, of well,
(20:17):
assuming that everything staysequal, which is like well, that
first assumption, if you raisetariffs, that's going to affect
other things in the economy.
Prices of goods are going to goup to the end consumer, which
is then going to Like there's,you're looking at that macro
level.
It gives you a perspective onkind of you know, broadly
(20:39):
speaking, how a business runs,but like you learn so much about
, like a very it's almost likean impeachment.
You're like dialed into onespecific aspect of the business.
Speaker 3 (20:50):
Yeah, so kind of the difference between understanding
and comprehending, where you,when you go to school, you
understand this material.
But until you're actually inthe workforce and using those
things that you learned andseeing how they intersect with
each other, that's where you geta comprehension of it.
Speaker 1 (21:09):
Well, okay.
So one thing you said before wehit record was you feel like
the MBA is a cheat code, and I'mnot trying to rain on your
parade by saying like you getlike a sterile kind of formal,
this is what.
But I will say the benefits ofan NBA is that you get a broader
perspective.
(21:30):
Yeah, because that person whowent and got the marketing
specialist just knows marketing.
Yeah, versus, like you'rezoomed out and you can.
You can kind of see like ohwell, you know we're marketing
really heavy for these areas,but we're having a supply chain
issue here.
So like it doesn't matter, ifthe marketing is effective in
(21:50):
florida, we can't ship anythingthere, it's just all going to
waste.
So like that's yeah it's kind ofa different game that you're
playing.
It's like almost you're gettinginto the world of strategy
versus in a marketing specialistrole.
You would be the executor, youwould be kind of running it and
then which I mean it?
You know we've talked for awhile.
Your goal is you want to moveinto management, right?
Speaker 3 (22:13):
yeah.
So when I said cheat code, whatI mean is I'm an analyst.
Now If you look at our orgchart, there are 20 people above
me, right, there is nobodybelow me.
How do I scale my career, right?
Do I just work as an analystand either job hop to eventually
(22:38):
get to a better position, or doI stay in my analyst role and
just, you know, grind it out andhope I get the promotions over
time and time and time and thenin 20 years I'm in a leadership
role where I can be an analystnow, get my MBA and then hope
(22:59):
that scales my career a littlebit, where maybe I can you know,
I don't know cut a couple stepsthere.
Or my next if I were to leavemy company, I would be able to
jump in at a higher role, right?
Yeah, who knows?
Speaker 1 (23:18):
This kind of circles back around to like.
One of the first things I saidwhen I was like opening the
podcast is there is an importantaspect that is neglected by
like I don't know 95 of peopleworking in analytics is building
relationships in the industry,and I will say an mba, a good
mba, so like, and I'm not evenwhen I it's funny when
(23:40):
university yeah when I say agood mba, I'm not even talking
about academics rightfunctionally speaking, a good
mba gets you plugged into anetwork and gets you because you
went.
Speaker 3 (23:52):
Yeah, I mean that's why I chose hp.
Speaker 1 (23:54):
Yeah hp is like very razzle-dazzle.
Speaker 3 (23:56):
Yeah, la-di-da.
Speaker 1 (23:57):
But I mean they have.
Devin Summers, who was in myclassroom here at Greensboro
College four years ago, wentdirectly from studying business
at Greensboro College gettingthe analytics minder, then
jumped directly into an MBA atHPU and then he got a senior
(24:18):
analyst role at NASCAR first jobout of the gate.
Speaker 3 (24:21):
That's awesome.
But the thing is like there's alot of stories like that too.
Right.
You know, I was razzle-dazzled abit whenever I did my tour of
HPU and instead of giving you apamphlet, they actually give you
these hardback books and theyhave all these, you know,
student success stories in theretoo, where their students are
(24:42):
getting internships, and that,ultimately, is what sold me,
because I could just go get apiece of paper and that's
probably not going to do for mewhat HPU would, where you would
get plugged into a network andget to meet people yeah, well, I
mean, I'm actually on theadvisory board for hpu's
(25:04):
business school.
Speaker 1 (25:05):
They have a whole like catalog of contacts of
former students and also peoplewho are like volunteering to
like work with hpu students andyou just go onto the Excel file.
It's got their telephone number, their email address, their
LinkedIn, so you can just go andreach out to them and connect
with them, which is I don't knowwhy all colleges and
(25:27):
universities are not doingsomething similar to that, but
that's hugely valuable becausethere's a whole hidden job
market out there where peopleare getting jobs because they're
not.
They're not even applying, it'sjust because, oh, the former
head of this department knowsthis.
This guy who works in analytics, he completely bypassed the
(25:51):
cold application process and gotdirectly to a you-round
interview because this personkind of vouched for him.
And you've got to bear in mindthere's dynamics at play with
that.
If that VP referred me to thejob and I had a bad job, that
would make him look bad, yeahabsolutely, and it would kind of
(26:13):
hurt his social capital, soreferrals are extremely valuable
.
Speaker 3 (26:20):
They are and I've ultimately a referral helped me
get my job now and it's I canconfidently say the position
that I'm in now is the first onethat I have where I really like
my job.
Speaker 1 (26:34):
Okay, that's a perfect conversation.
What does that mean?
Like what, and you don't haveto get into like this.
I don't want you to like throwanybody on their bus, but what's
a good job, what's a bad job,or what aspects make it good or
bad to you?
Speaker 3 (26:50):
Okay, Well, what I like about my job now is I love
my team.
I love the team that I workwith.
We help each other out.
There's no stupid questions.
There's a lot of like knowledgetransferring sessions.
Like hey, you want to learnthis?
Like let's hop on a call andwalk through this.
Or you have a question aboutthis?
Like let's get together andtalk about it.
(27:13):
I love that aspect of teamworkand team building.
I've seen growth in my rolewhere I haven't seen growth in
other positions.
Speaker 1 (27:25):
So it felt just like static, like there was no that.
I can see that as being verydemotivating of like absolutely
there's no room for growth here,so I'm just going to put in the
bare minimum, because I'm justwaiting for the next thing yeah.
Speaker 3 (27:38):
Yeah, yeah.
So there's that.
There's a lot of cross training.
I love being hybrid.
Yeah.
Where my office is.
It's like 10, 15 minutes away.
I go in about once a week andwe actually play Dungeons and
Dragons on our lunch break onWednesdays, which I absolutely
(27:58):
love.
So there's such a great culture.
It's a good snack If I need tostep out and run an important
errand you know nobody's goingto be like.
Did you put in your time forthose two hours while you were
doing this?
Or I called you and you didn'tanswer you're not micromanaged.
(28:19):
I'm not micromanaged.
I feel like an adult, yeahthere.
Speaker 1 (28:25):
I think there's also an aspect, too, of finding the
right kind of work as well.
Um so, do you enjoy the workitself?
Speaker 3 (28:34):
I really do, I really do so, I work in real estate
technology.
Speaker 1 (28:38):
You're like lighting up, talking about work.
Speaker 3 (28:41):
I know, isn't that funny.
Speaker 1 (28:42):
Yeah, that's awesome.
Speaker 3 (28:43):
I love it.
I work in real estatetechnology and I feel like in a
past life maybe I was a realtoror an interior designer or
something so I really enjoy thedata that I work with.
I think that makes a bigdifference too, because when I
worked at a CPA firm, it wasjust numbers.
Speaker 1 (29:01):
Accountants are some of the most flavorful, colorful
people I've ever met.
Sorry if you're an accountant,I'm not trying to like poo-poo
on you guys.
Speaker 3 (29:15):
What makes where I have been unhappy, what makes a
job not desirable, I would saywould be it was such a
high-stress work environmentwhere it was every single day.
We had a deadline to meet byfive o'clock but we couldn't
start.
You know pushing the data to gowhere it needed to go until
(29:35):
like 3.30.
Speaker 1 (29:37):
So you had like an hour and a half to get the thing
done.
Speaker 3 (29:39):
Yeah, if there was an error which errors happen all
the time it's like, okay, well,now you're working until 8 pm
every single day and my workschedule was like I was my
busiest from 3 pm until 8 pm.
Every day is what it felt like,and I was also super busy in
the morning.
So I'm still starting at 7.30,8 o'clock in the morning.
(30:00):
Oh wow, and it was just theselong days.
It felt like thankless work, tobe honest.
Okay, and a culture ofhostility where everybody was
just frantic.
I will quote this one thingthat someone said to me one time
.
Speaker 5 (30:19):
It's comical, it's in a call and they said I feel
like there is a train coming andI am standing on the track and
I know it's not going to stopand I'm just hoping that me
standing there will slow it downand ultimately I am going to
(30:40):
get run over and started tearingup, wow, and this was like a
senior level person and I waslike, yeah, this is awful,
because I feel.
Speaker 3 (30:52):
I mean, I don't feel like that, but I felt very
stressed and that's I rememberthe day I quit, or like my last
day there.
I didn't just quit, but I sleptall night, yeah, and I forgot
that I could do that yeah, Imean that's.
Speaker 1 (31:11):
That's a whole other aspect of like keeping an eye on
your mental health, like ifyou're not sleeping through the
night because you're so stressedabout work, that's beige,
probably a red flag.
Yeah.
Like I don't know.
I mean, maybe there's othercircumstances that are kind of
complicating things, but yeah,I'd say it's a red flag for sure
.
Yeah.
Speaker 3 (31:30):
I wouldn't say because you dream about work.
That's a red flag.
Like I, sometimes I dream thatI'm working now and it's still
stressful yeah like, especiallyif I'm kind of in the middle of
a problem that I'm working on,or like a project that is time
sensitive.
You know I'm thinking about it,but uh, it's definitely well, I
(31:51):
mean it's, it's sound.
Speaker 1 (31:53):
The assumption I'm making about that role that you
were in in the past is thatwhat's the saying?
Shit rolls downhill.
It sounds like.
Speaker 3 (32:01):
I have never heard that, but I would assume it does
.
Speaker 1 (32:05):
It sounds like the CEO might be under pressure from
the board and there might besome weird political stuff going
on, like maybe there's acorporate takeover and like
these people are trying to clingto like their job, and then
they put pressure on theirdirect reports and then their
direct reports get pressed andit's yeah, so we?
Speaker 3 (32:23):
what I was doing was covid rental relief
disbursements.
I think ultimately it wouldhave been a temporary position,
any like there's a lifetime tothat role, um, but you know,
banks close at five o'clock soyou get in everything you can
until the end of the day.
So really that's just how thesystem worked.
I don't know if there's abetter way around.
(32:44):
That.
That's above my pay grade, Iguess.
Speaker 1 (32:48):
It's something I don't like to say.
Yeah, but I mean you're gettingan MBA so soon to be not right?
Speaker 3 (32:52):
Right.
Speaker 1 (33:00):
I'm ready to take on anything now with my pay grade
just so I can learn more.
All right, so what classes areyou taking?
Speaker 3 (33:03):
I know you looked this up like right before I know
I said I should be able toanswer this.
Well, I finished on mymarketing based management class
.
I'm taking a supply chainoperations class and this is
what I looked up and I alreadyforgot what it was.
I think it's accountingfundamentals is the other course
(33:24):
, so that's like theprerequisite course and it's a
self-paced course.
So initially when I started myMBA, I wanted to do it full-time
so I could finish in a year andI thought a good way to test
the waters to see if I canmanage a full, if I could go
full-time, would be to.
I'm going to sign up for thisone class and then I have this
(33:45):
self-paced course at the sametime so I can finish that
whenever I want to.
I ultimately need that before Ican take other classes.
That did not work no.
I am could not handle theworkload of working full-time
and taking two MBA classes.
Yeah, it was too much.
(34:05):
It was too much, so I'm stillworking on that self-paced
course now alongside my supplychain class.
Speaker 1 (34:13):
So I mean this is a bit of a tangent, but how would
you rate your time managementskills out of 10?
Speaker 3 (34:20):
I would say if you asked me that question a few
months ago, I would say one ofmy weaknesses would be time
management.
But I think I've gotten to areally good place where I manage
my time really well.
I'm really good at blocking offmy calendar and my schedule
personal and work to make sure,like if something gets in yeah,
(34:42):
I can get it done, but what mybigness weakness is is based off
of that, and I don't even knowwhat you would call this is that
when something unexpected comesup now, that will sometimes
throw me into a frenzy.
Yeah, yeah, yeah.
Where I'm like, that willsometimes throw me into a frenzy
.
Yeah yeah, yeah, where I'm like.
Oh man, I didn't account forthis.
Right.
And now I have to, like I'vestacked up my time and yeah.
(35:06):
So I guess to mitigate that,like what I've done is I try to
get everything done Monday toFriday, so my weekends are my
weekends.
Yeah.
And if something comes up, thenI can.
Speaker 1 (35:16):
I mean you may also want to like bake in some safety
time.
Yeah.
Almost like an emergency fund.
You know like having a three tosix-month emergency fund makes
your finances so much lowerpressure.
Yeah.
But at the same time, though, ifyou're taking two classes and
you're working full-time and youhave a social life, yeah, I
mean, I don't know, my weekendshave become you're doing a lot
(35:45):
like right now it's you're.
You're getting used to beinglike very busy and I think that
that's stretching you in a goodway yeah, I hope so, I'd imagine
.
Speaker 3 (35:55):
I hear all these senior positions are working off
the wall hours.
So if I, if I'm filling up mytime with that many hours, then
if I could just do one thing forall of those hours, maybe that
would be easier.
Speaker 1 (36:12):
As you're moving kind of up a hierarchy, I think you
have to deal with broader setsof problems, or I mean and I
guess this is anotherconversation, living back to
what we were talking about withyou know, getting growing in
your career, like there are twopaths kind of within analytics,
so like you could move intomanagement, or you could become
(36:35):
like a highly specializedindividual contributor.
Yeah.
Where you're doing like I'mtrying to.
Speaker 3 (36:40):
I wouldn't mind that either, honestly.
Speaker 1 (36:43):
Which like, but I feel like being an individual
contributor might kind ofconflict with the nature of an
MBAba, because the nature of anmba is kind of wide, yeah versus
a getting a like a phd ingeospatial science, like what is
.
Isn't that what kinga has?
Geospatial she has like a phdin like environmental science,
like focusing on, like geographythat sounds she now is a data
(37:06):
scientist that works for a floodrisk startup.
Yeah.
I mean that's like think abouthow specialized that is, like
you've studied this forenvironmental stuff, for I don't
know.
Speaker 3 (37:17):
A PhD.
Oh my gosh.
I hear those can take two yearsto more.
Yeah, like do they take youfive.
Speaker 1 (37:26):
So that's like an area that she studied and she's
become an expert on and then sheconsults in that space, versus,
like, going the nba route.
Yeah, you might have to.
There are certain threads thatare going to span multiple kind
of verticals and departments,and higher up the organization
you go, the more you kind ofhave to to deal with that yeah,
(37:49):
yeah, absolutely so yeah, it's.
It's just, I think, you'rehaving to deal with like more
uncertainty as well, you knowwhich, and that, I think takes
the ability to kind ofself-soothe and deal with
anxiety, which sounds likeyou've also gotten better at
that too.
Speaker 3 (38:08):
Yeah, I would say so.
I think me going to the gym isa big part of that, and then,
unfortunately, with my schedule,now that's not something I'm
able to do like I was, butmaking sure that I get there at
least once a week it does help,for sure.
For sure.
Speaker 1 (38:28):
I got you.
Okay, once a week is it doeshelp.
Speaker 3 (38:30):
For sure, for sure, I got you, so okay, so you're a
semester in or two, technicallyyeah, so two mini masters in
which would or like the secondhalf of one mini master in the
first half of another, I mean.
Speaker 1 (38:42):
I'm just one.
I'm kind of curious, Like doyou have like a specific title
or direction that you want to goin?
Speaker 3 (38:58):
Because I feel like there are a lot of people who
have the same kind of instinctthat you have of like, oh, if I
get a master's degree, that'sgoing to open doors up for me.
Yeah, it's interesting.
I did this HPU MBA summit.
I met a lot of the otherstudents and I was very
impressed how many people knowexactly what they want to do and
I don't.
But I think I'm just going to.
I'm still trying to figure itout.
(39:20):
I know that I want to be abridge between.
I'm not the most technicalperson in the world.
Obviously, Like I said, I'm notgoing to be a full-stack
developer or anything, but I canbe more technical than most and
have that business acumen andbe able to be in a leadership
role where I can convey whatneeds to be conveyed and, you
(39:42):
know, do the thing.
I guess If I had a title inmind, I don't ever want to be a
CEO, but wouldn't it be cool ifI was like a CIO or, you know, a
CTO?
I don't know, Maybe I need tobe more technical than what I'm
imagining, but I'm still tryingto grow my technical skills.
In the position that I'm in now, I still have the opportunity
(40:04):
to learn a lot of new things andI am actively learning every
day on the job.
So I'm hoping, as that growsand then by the time.
I get my MBA.
Maybe there's also the impostersyndrome, like I don't know.
Probably won't ever be goodenough for that, but if I aim
for it, we'll see where I fall.
Speaker 1 (40:20):
You're cracking me up a little bit because you just
said I don't know what I want todo and then proceeded to give
me a very detailed breakdown ofwhat you want to do, so like I
don't know.
If that's fair.
Like well are the people thatyou're like that were in that
orientation, where they like Iwant to be at this specific
(40:40):
company at this pay.
Like that feels a little rigidto me.
Yeah.
It's like your, your kind ofvision for like where growth
could go or where your careergrowth could be, feels kind of
realistic, like it's not.
You know, I need to get a jobat Meta and that's success.
Yeah.
Because it's like you get inthere and then what you know
(41:00):
like that's yours, seems kind ofa little pliable A little bit
pliable.
Speaker 3 (41:06):
Which is just more realistic.
I would hope so.
Yeah, and I like working intech now and I would be
interested in other fields too.
Just hearing about the freshmarket honestly.
Yeah, first of all, that 40%discount.
Speaker 1 (41:22):
I don't know if I can say that on air, but that's
incentivizing, I mean, I guessthat's like free promo for them.
Speaker 3 (41:28):
Yeah, I have friends that do really well in retail
too, and I think that's superinteresting as well.
Personally, I love retail, I'ma shopper, I love Target.
Speaker 1 (41:43):
Okay, well, I mean, it sounds like you.
Speaker 3 (41:45):
I feel like I am very adapt, adaptable and I can find
happiness in a lot of places.
Um so, in the space that I'm innow, the the real estate.
It's not what I would have ever, it's not what I expected or
ever aimed for, but, right, it'scool.
I really like it, I really likeit um, I know what I don't like
.
I I don't want to work for afinancial institution.
(42:06):
I know I don't want to work forany.
I don't want to work for afinancial institution.
I know I don't want to work forany pharmaceutical company.
Never would want to work forthe government, like any sort of
government sector.
So yeah, I mean I have a littlebit of direction, like I know
enough to stay in a lane, butyou know I would be willing to
take multiple paths.
Speaker 1 (42:27):
Well, you have a lot to build off of.
You know a lot of experience,like a lot of skills and
knowledge, because I was talkingwith somebody I think it might
have been a student of how manypeople know Excel.
You know probably, like Idon't't know Excel at all
(42:48):
probably 95% of corporate people, but how many people know it
above a 5 out of 10?
Yeah, then that breaks it downto like I don't know 20% of
people but it's.
Speaker 3 (43:00):
I feel like that brings us into the conversation
of AI, because Excel I thinkit's Excel right, they have a
new AI assistant that you canuse, whereas, basically, if you
know the basics, if you knowwhat questions to ask, then you
can do anything which.
I feel like that was truebefore.
You just had to be willing todo your due diligence and
(43:21):
research to be like how do Icreate a dropdown menu?
Right now, you could just usethe the tool and it's going to
go ahead and make it for you, uh, but I wonder, does that raise
the bar?
You know if everybody can do nothat was another, um uh,
incentive for me to get my mbatoo, where like to set yourself
(43:44):
apart yeah, I don't know if Ican keep up with.
I don't know if I can keep upwith tech has?
Speaker 1 (43:52):
has daniel hall not told you his whole take on ai?
No, tell me um, ai is not goingto replace your job, it's just
going to augment it yeah, butmore people are going to be able
to do that job.
Speaker 3 (44:02):
Now, that's what I think um and empower more people
to be able to do.
Speaker 1 (44:07):
I think you are undervaluing the fact that you
have a five-year-long history ofworking with data, the critical
thinking ability that youdeveloped, and like the
intuition and asking the rightquestions, you know, like
because, yeah, the new thing isgoing to be prompt engineering.
But the fact that you've workedwith data and you're like, oh,
(44:30):
this data looks wrong, so it'slike, okay, why might this data
be wrong?
Oh, it's because this table'snot joined correctly, so you can
go and follow the thread,versus, like, some average
person might not even be able torecognize mistakes.
They're just going to ask hey,you know why were sales down
(44:50):
last week?
And then it would give like asee, I'm not so sure that like
AI, is this super pill?
Like there's so manyassumptions and there's so much
like gray, that like.
Speaker 3 (45:04):
I feel like it's going to change.
It is already changing a lot ofthings.
Speaker 1 (45:06):
It will change the nature of work.
Speaker 3 (45:08):
yeah, For example, in my role as a data scientist,
one of the last things I wasworking on with my team was
creating a new API connection tothis new platform we were using
In my role.
Now I wanted to connect to anAPI to pull specific data.
(45:28):
I went to chat GBT Obviously Idon't use this on my work
computer, but I'll use it on myregular computer and then, you
know, copy the script over.
But I went to chat GBT saidconnect me to this API, I want
to pull this, this and this, andthen I am able to just set up
my connections with mycredentials and the data's there
(45:52):
.
Where.
That took like my team beforewe were working on creating this
API connection for like a monthor two and it took me 15
minutes.
Speaker 1 (46:03):
That's crazy, yeah.
To do it now, Well, that's ahuge amount of leverage.
15 minutes that's crazy.
Yeah, Do it now Well, that's ahuge amount of leverage.
But the problem with leverageis it can go both ways right.
Like if I'm buying a short forthe housing market in 2007,
that's awesome.
But if I were, you know, if Ileveraged some cash to go and
buy a house in 2007, I would beout, I don't know, probably a
(46:28):
few hundred thousand dollars.
So, like AI can be really good,it also can be there's a
liability or a risk to it.
Yeah.
Speaker 3 (46:35):
Because if you're just going off of what it's
telling you without fullyunderstanding, like, hey, this
checks out, this makes sense,and like understanding the use
case and the contributingfactors to why you know things
might be this way or that way,yeah, um so I guess how you were
saying I was underplayingmyself before, like I think I do
still like believe that it'strue that more people are going
(46:56):
to be able to do those likebasic to intermediary yeah, or
intermediate skill level taskslike with an Excel or BI
assistance, tableau assistance,whatever.
But I think also there's thatscalable too.
So if you're at a level three,maybe you can jump to a level
(47:18):
five where you wouldn't be ableto before.
So maybe I should look at it atthat perspective instead of
like oh no, I'm a level three,everybody's about to be a level
three.
Speaker 1 (47:31):
You know what I'm saying.
Yeah, I think you'redownplaying yourself.
I think it might be someimposter syndrome um, I don't
know that's.
I think you're in a great spot.
You know, like you've you'vegot five years of experience is
very, very important or very keyright now.
Yeah, because it's, it's veryhard to break into analytics
(47:51):
right now.
Is it?
It's, it's gotten.
I mean, I shut down my careerservices program cause I, you
know, I had a hundred percentmoney back guarantee and it was
like same program, samemethodology.
You know, about a year ago Iguess, like, oh, like, maybe a
year and a half, two years ago,at this point the job market,
(48:11):
especially for entry level, justkind of tanked.
Speaker 3 (48:15):
And you know what I have found is being an analyst.
I still do believe that it'slike a commendable title.
However, I feel like it'sbecome like it's getting diluted
right.
Speaker 1 (48:26):
Yes, it's become this diluted right.
Speaker 3 (48:27):
Yes, it's become this buzzword essentially.
I know, uh like my company dida restructure of positions and
now it's like everybody's ananalyst.
Speaker 1 (48:38):
Yeah.
Speaker 3 (48:39):
Everybody's an analyst Well and.
I see that, and just looking atother jobs online too, uh like
there's a financial analyst.
I'm reading what's required andit sounds like a typical
analytics job.
And then I go to the next oneand it has nothing to do with
analytics.
Speaker 1 (48:56):
Yeah.
Speaker 3 (48:58):
And.
Speaker 1 (49:00):
There is some kind of like, but at the same time
titles are somewhat arbitrary.
Like for, for example, youmentioned, like the banking
industry, apparently it's likenot that hard to become a vp,
like a like, yeah, like, becauseI I think that, or maybe I
shouldn't say it's not that hard.
But a vp at the fresh market isyou're one level below c-suite,
(49:23):
but a vp within like I don'tknow, truest, for example, I
think there's like multiplebusiness units.
A vp is like a manager or adirector level, maybe more
accurate to be a director level,because then there's like
senior vps and then there's likeI don't know so that also gets
you back to like what size isyour company essentially?
Speaker 3 (49:44):
too yeah like there's a lot of intermediate, there's
those small companies, there'smeta, and then there's so many
in between where I don't think Iwork for a huge company per se,
definitely not like meta.
Yeah.
But there's still at least 10people above me.
Speaker 1 (50:05):
That's crazy.
I'm trying to think about, like, in my current position, how
many people are above me.
I think there's only like two,three levels of management above
me, maybe two look at you, bigshot well, but it's a different
I.
I think it's a flatterorganization maybe, and that's
see that that we could go onit's.
It's an endless conversationaround, like you know what's the
(50:27):
size of your company, whatindustry are you in, what
vertical within that industry.
So yeah, but I guess I'llcaveat this of like, if you're
getting a new job, they don'texpect you to know everything,
but if you have like a history,if you have five years of
working with data, variousdifferent companies, various
(50:47):
different industries, that givesyou a starting point, that
gives you a leg up over, youknow, people who are just
starting out, entry level, thathave access to AI.
I feel like you're downplayingthat.
I'm trying to like pump you upa little bit, but you've got
this body of work, theseexperiences, these skills and
(51:09):
these wins, quite frankly, thatare kind of mental models in
your head that you can use tonavigate.
Speaker 3 (51:15):
Yeah, yeah, I mean, ai is definitely here to stay.
So I think that's somethingthat everybody's going to be
using, and even my husband'scompany.
They have an internal AI fortheir whole organization and
it's been incredibly useful tojust say, like go in and you can
ask, right that's crazy overthis project and it will pull up
(51:37):
this.
Or, like you can ask questionswhere you might spend time, you
know, going through the officeor he works in manufacturing, so
going from this person to thisperson to this person to try to
figure out an answer where youcan use the AI now and that's
not enhancing anybody's job aslike as a skill set, essentially
(52:00):
, but it is enhancing your job,the time you would spend doing
certain things and increasingaccuracy.
Right.
Reducing bottlenecks.
I guess you could say wherelike people might get stuck and
be going to the wrong person.
For this one thing, thisproject is getting delayed or
not.
All the information is thereand now this ai tool is there to
(52:21):
like, let the data flow orsomething.
Speaker 1 (52:27):
Yeah, I feel like AI is where analytics was.
When you and I first sat downat Mythos on Market Street in
Greensboro the beginning andlooked at Because I mean, I feel
like you got into the analyticsmarket at a really good time.
Speaker 3 (52:42):
I think so too, you know like Because I remember I
was really wanting that analystposition and I didn't get an
analyst position right away yeah, a data mining position.
But I thought, okay, well, thisis good I.
Speaker 1 (52:55):
I took a data mining class in my gis course in
college, so I was like you knowright, but I mean, even that is
like enough of an end to likelook, look, what you've done.
Speaker 3 (53:06):
It's working with data.
Yeah, you know like it'sworking with big data.
Right.
It's such a valuable thing,it's such a transferable skill.
Speaker 1 (53:16):
I gotcha All right.
Well, let's wrap this bad boyup.
Do you have any closingthoughts on how people can get
an analytics job?
Speaker 3 (53:25):
Craig's sitting right here off screen what do you
have to say to Craig Just beopen, you know.
Yeah.
Like if there is one thing thatyou know that you want to do,
definitely go for it, but don'tbe afraid to take a baby step
first and then jump from thereLike just get in.
Speaker 6 (53:48):
Yeah, yeah, I definitely.
That's kind of the advice thatI'm hearing from a lot of my
professors nowadays is, ifyou're a really smart person, if
you have critical thinkingskills you know there's not a
good way to show that on yourresume and your application, but
if you just get in, if you'rean impressive person, you will
impress somebody.
Speaker 1 (54:12):
And you just have to get that personal, you just get
in you know if you're animpressive person.
You will impress somebody andyou just have to get that
personal.
You just have to get in.
Well, good luck on yourinterview on monday.
Thank you, I mean craig's anoverachiever, if you do, you
mind me.
Yeah, we can talk about that,all right.
So you got an interview for uh,is it like essentially like a
project management?
Speaker 6 (54:24):
uh, it's a it's a project management position at
an architectural design company,but the deal is kind of it's a
growing position and so if aproject manager like this will
be the first time they hiredsomebody to do that, so that
person also needs to know someanalytics.
They need to know we're gettingall these new numbers.
It's the first time thecompany's had all these numbers.
(54:44):
Somebody needs to know what todo with all these numbers,
because that's like a freshthing to them.
Speaker 1 (54:50):
Well, you said you read a book on architecture in
the last two days.
Speaker 6 (54:54):
Yeah, well, I've been studying up, so I went to Books
A Million and got a copy of abook on the architectural
business.
Speaker 1 (55:02):
It was like 200 pages .
Speaker 6 (55:03):
It wasn't architecture for dummies.
No, I didn't pick uparchitecture for dummies.
There was project managementfor dummies.
Yeah, you sent me some picturesof that.
That was funny, but I don'tknow.
I've actually read some of thefor dummies books and they're
kind of like for dummies, youknow.
Speaker 3 (55:18):
It helped me pass chemistry.
I will say that I've got achemistry for dummies alongside
my textbook Gotcha for dummiesalongside my textbook Gotcha I'm
a dummy there.
Speaker 1 (55:28):
All right.
Well, molly.
Thank you so much for your time.
Craig, good luck on Monday.
I know you're going to kill it.
And thank you all for tuning into the episode.
Speaker 3 (55:36):
Thanks for having me.
Popular Podcasts
Las Culturistas with Matt Rogers and Bowen Yang
Ding dong! Join your culture consultants, Matt Rogers and Bowen Yang, on an unforgettable journey into the beating heart of CULTURE. Alongside sizzling special guests, they GET INTO the hottest pop-culture moments of the day and the formative cultural experiences that turned them into Culturistas. Produced by the Big Money Players Network and iHeartRadio.
On Purpose with Jay Shetty
I’m Jay Shetty host of On Purpose the worlds #1 Mental Health podcast and I’m so grateful you found us. I started this podcast 5 years ago to invite you into conversations and workshops that are designed to help make you happier, healthier and more healed. I believe that when you (yes you) feel seen, heard and understood you’re able to deal with relationship struggles, work challenges and life’s ups and downs with more ease and grace. I interview experts, celebrities, thought leaders and athletes so that we can grow our mindset, build better habits and uncover a side of them we’ve never seen before. New episodes every Monday and Friday. Your support means the world to me and I don’t take it for granted — click the follow button and leave a review to help us spread the love with On Purpose. I can’t wait for you to listen to your first or 500th episode!
Dateline NBC
Current and classic episodes, featuring compelling true-crime mysteries, powerful documentaries and in-depth investigations. Follow now to get the latest episodes of Dateline NBC completely free, or subscribe to Dateline Premium for ad-free listening and exclusive bonus content: DatelinePremium.com