April 8, 2025 • 34 mins
Cindy Clifford, a seasoned educator of 25 years, refused to let age or past career define her. She used her skills honed as a teacher and pivoted to data analytics! If you feel you're too old to pivot and become a data analyst, it's never too late-- dive into Cindy's story.
💌 Join 10k+ aspiring data analysts & get my tips in your inbox weekly 👉 https://www.datacareerjumpstart.com/newsletter
🆘 Feeling stuck in your data journey? Come to my next free "How to Land Your First Data Job" training 👉 https://www.datacareerjumpstart.com/training
👩💻 Want to land a data job in less than 90 days? 👉 https://www.datacareerjumpstart.com/daa
👔 Ace The Interview with Confidence 👉 https://www.datacareerjumpstart.com/interviewsimulator
⌚ TIMESTAMPS
00:00 - Introduction
01:26 - Burnout with teaching.
11:34 - Cindy's first data role.
13:04 - FindADataJob.com and PremiumDataJobs.com.
19:14 - Cindy's second data job.
30:10 - Advice for teachers who want to become a data analyst.
🔗 CONNECT WITH CINDY
🤝 LinkedIn: https://www.linkedin.com/in/cynthia-a-clifford/
🔗 CONNECT WITH AVERY
🎥 YouTube Channel: https://www.youtube.com/@averysmith
🤝 LinkedIn: https://www.linkedin.com/in/averyjsmith/
📸 Instagram: https://instagram.com/datacareerjumpstart
🎵 TikTok: https://www.tiktok.com/@verydata
💻 Website: https://www.datacareerjumpstart.com/
Mentioned in this episode:
💙 Thank you for subscribing & leaving a review
Thanks to YOU we recently became the most popular data podcast out there. Thank you so much for listening. If you haven't subscribed yet, hit subscribe. It costs $0. If you enjoy the show, leave us a 5-star rating on Spotify or Apple. It helps people like you find the show AND it helps us land better guests. Thank you so much for your support.
Join The Next Cohort of The Accelerator
Want to land your first data job? Join my data bootcamp to get EVERYTHING you need to land your first data job! Excel, SQL, Tableau, Power BI, Python, R? Yup. Projects? Lots of them. LinkedIn help? Of course. Resume optimization? You betcha. Job hunting strategy? Duh. Click to learn more!
Mark as Played
Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Avery Smith (00:00):
This is Cindy Clifford.
(00:01):
And Cindy was a teacher andeducator for over 25 years until
Cynthia Clifford (00:06):
I reached a real burnout stage with teaching and I knew
I needed to do something different.
Avery Smith (00:12):
And honestly, can you really blame her teaching is really,
really hard in the first place.
But Cindy was not only a teacher, shewas an international school teacher
and endured some pretty crazy thing.
Cynthia Clifford (00:23):
I was stuck in a military coup in Myanmar,
and then I went to Vietnam andI got stuck in Covid Lockdowns.
I spent a year teaching online withoutbeing able to leave my neighborhood.
Avery Smith (00:34):
Yeah, that's not fun at all.
Being a teacher is hard,but here's the truth.
Teachers make great data analysts.
In fact, most teachers are already kindof analyzing data one way or another.
Whether they realize it or not, teachers
Cynthia Clifford (00:48):
are constantly evaluating and assessing the situation
and our problem solving and dataanalysis really is about problem
solving and communicating the resultsof the problems you've solved.
Avery Smith (01:00):
In this episode, Cindy and I will explore her
data career story and what helpedher leave a career of 25 years.
Ultimately become a data analystat a company like Impossible Foods.
Thank you so much for subscribingto our show, and let's go ahead
and dive into this episode.
Alright, Cindy, you studied engineeringin college and then you had a 25 year
(01:20):
career in teaching all over the world.
What made you wanna become a data analyst?
Cynthia Clifford (01:26):
I wanted to become a data analyst because, well, partly,
and I know you've had other teachersthat in the program, I reached a real
burnout stage with teaching and I knewI needed to do something different,
and I'd known that for a while, but itreally reached a height, as you said,
I was teaching all over the world.
I was stuck in a military coup inMyanmar, and then I lost my job,
(01:50):
and then I went to Vietnam andI got stuck in Covid lockdowns.
I spent a year teaching online withoutbeing able to leave my neighborhood.
None of that was goodfor my mental health.
And I came back to the USafter that summer and I said,
alright, you gotta figure it out.
You absolutely have tofigure out what you wanna do.
And I spent the summerinformational interviewing.
(02:11):
I met.
Kind of everybody under the sunmade connections on LinkedIn,
asked them if I could ask abouttheir job and what they did.
I first thought I would want to do thekind of things that a lot of teachers
transition into, like, uh, instructionaldesign or learning and development
in a corporate environment, and.
Still realized that that wasn't thedirection I wanted to go, and I, you know,
(02:35):
I taught high school math and statistics.
I always, the math wasalways my favorite subject.
And data analysis started tomake, make a lot more sense.
I reached out to a, a formercolleague who's still a friend.
Who had already made that transitionand he's now a data scientist.
And he and I talked a lot aboutwhat I needed to learn and what
some of the ways to learn were.
(02:57):
And I decided I was gonna go for it.
So my last year of teaching overseas inVietnam, I spent weekends and evenings.
I started with the, the Google DataAnalytics certificate, and that confirmed
that I wanted to go in that direction.
But when I found you, I was really gladbecause I knew that I wasn't really, it
was like taking little quizzes and I'm,I'm a good student, I can do that, but
(03:21):
I knew that I wasn't really learning.
To do things in a way thatwas gonna help me find a job.
So
Avery Smith (03:27):
it makes a lot of sense 'cause my mom's a teacher.
Being a teacher, I mean, obviouslyyou're making a difference in kids'
lives and that's very meaningful andwe appreciate all of our teachers.
But being a teacher kind of sucksa lot of the time for many reasons.
Like you said, long hours, lowpay, and it can be just like.
Very stressful and, andfatiguing, so it makes sense.
You, you found somethingin, in data analytics.
(03:48):
You're like, okay, I'm good atmath, I'm good at statistics.
Let's do, let's do this and find alittle bit more of a calmer career.
Start off with the Google search.
I had forgotten about that and I.
And I like what you said, it would likeconfirm that like, okay, this is something
I wanna do moving forward, but didn'tlike, feel like it prepared you for a job.
Do you remember, I, this isgoing off script here, but do
you remember how you found me?
(04:08):
Like this was, this was a while now'cause you've been in your, in your
career now for what, almost two years?
I think so.
Yeah.
A
Cynthia Clifford (04:15):
hundred percent no.
But I know that I had startednetworking on LinkedIn and
reaching out to various people andmaking connections and comments.
None of it's supernatural to me,but I was already doing that and.
Following people and finding peoplewho had made the transition to data
who were formerly teachers, andsomewhere or other I came across your.
(04:41):
One of those come and listen tothe, my program, you know, talks
that you were running, what youwere saying made a lot of sense.
You know, I am kind of cheap and I waslike, Hmm, is this like legitimate or is
this, you know, one of these 'cause somany sort of scammy things on LinkedIn.
(05:02):
But I somehow, I trustedand I'm glad I did.
Avery Smith (05:06):
Good.
I'm, I'm glad you did as well.
Like you said, you kind of spent,uh, that last year of teaching
ramping up to, for this transition.
And I remember, I remember seeingyour, your comments in the community
late nights, I guess for, for meor or I, and for you, because, uh,
of the time difference, we usuallyhave live calls like at 7:00 PM
Eastern Time and for a while I,where were you and what time was it?
(05:28):
'cause you came to alot of our live calls.
Cynthia Clifford (05:29):
I wasn't able to go to a lot of those.
I was in Vietnam and it was like.
Seven in the morning for me, butI was already on my way to work.
Avery Smith (05:38):
I, I remember you coming to a couple in, in the mornings,
um, and you might be, well that's
Cynthia Clifford (05:43):
to then after daylight savings or something.
Ah, then it became six in the morningand I could go for an hour or for 50
minutes of it, and then I had to leave.
Avery Smith (05:52):
Perfect.
You were very dedicated and you,you did, uh, a lot of good research.
Were you nervous to makethis transition though?
Because you had been teaching forover 25 years where you're like, can
I really just reinvent myself again?
Cynthia Clifford (06:03):
I was definitely nervous, but I was also fairly feeling
fairly, like I just couldn't go onteaching and I had decided I wanted
to move back to the US and I did notwant to be a teacher in the US 'cause
I thought that would've even beenworse than being a teacher overseas.
Being a teacher overseas had beenreally good for a long time until it,
(06:24):
it wasn't, I didn't know exactly howlong it was gonna take you to find
a job, but I had saved up transitionand felt like I had a bit of a buffer
that if it also felt like, 'cause Iwas already older, like it was sort
of like, well, it's not now when like.
Like, I, I have to do it.
Like, so
Avery Smith (06:43):
I love that attitude though, because I feel like a lot of
people would just be like, ah, too late.
You know?
Um, but like, life's long andyou're also a very healthy person.
We've talked in the past, uh, youknow, about, uh, you try to, try to eat
healthy, try to exercise, stuff like that.
I.
Like life's long.
Like we have an opportunity, you know, we,we have to work, we have to go to work.
It's a big part of our lives.
(07:03):
Like, you know, you're spendingprobably like around eight hours
a day working everyone, right?
And you want to be doingsomething you enjoy.
You don't wanna be miserable.
Like if you're miserable now, like in1, 2, 5, 10 years, like, what's going
to change if you don't make a change?
And, and even if like the besttime to plant a tree was 10
years ago, the next best time.
Is today.
(07:24):
So I just wanna commend you forbeing brave, because I think a lot
of people wouldn't be brave andbe like, ah, oh, well I, I tried.
Cynthia Clifford (07:31):
Yeah.
No, I, I, but I, I am, I think in a lotof things, I have that attitude that
it's never too late to try new things.
I mean, I learned to cross countryski this year and working from home
in, in a cold climate like Vermont, I.
Spend too much time indoors in the winter.
So I decided this year that Iwas gonna learn to do a pull up
(07:51):
and put a pull-up bar outside myright where my office door is.
And every time I leave the room and tocome back, I have to practice a pull up.
I can now do a pull up.
Like, it's never too late to, to just try.
Like, otherwise you might as well, likeyou said, just curl up and it's done.
Avery Smith (08:09):
Be miserable.
For those of you, uh, for everyonelistening, you can definitely
tell what type of student, uh,Cindy is because she is ferocious.
Uh, you know, she's, she's willingto do, she's dedicated, she's, um,
consistent where she's like, even ifit's just one pull up, you know, I'm
just gonna try to do that one pull up.
Or if it's just a half, I'mgonna do the half pull up.
And that's how she was as a studentinside the accelerator program as well.
(08:31):
And I'll have to say, you kind of hadto be, because you were transitioning
from obviously not a tech field,like teaching is not a tech field.
And I'd almost argue that beingin education is almost like
a non-corporate field, right?
Like jobs aren't the same in the educationworld as they are in other industries.
Just because like it's,things are just different.
Like LinkedIn's not a thing and youget a lot of jobs from your district
(08:54):
or this and that, or like you're.
I don't know who, you know, yourprincipal or whatever, plus like you
weren't even in the us you hadn't evenbeen really in the US for a decade.
And so, you know, you joinmy program, you're like great
Avery's, SPN method I'm in.
And like the third part of the program,33% of the program is networking.
You're like, uh, I'm a teacher who'sbeen living overseas for a decade.
(09:16):
My network is, uh,maybe not the best ever.
So I just, I just wanna give youlike some credit for one being like
ferocious and battling through that.
'cause once again, a lot ofpeople I think, would use
that as an excuse and give up.
But like how did you network withlike this education and international
background that really maybewasn't super helpful for you?
Cynthia Clifford (09:35):
Well, I had actually found a program before
I found yours, which is how Istarted getting into LinkedIn.
I.
That program has is somethingthat helps teachers transition out
of teaching and there's a bunchof lessons including networking.
And I had been taking actionon that before I met you.
I was joining data groups and I.
(09:58):
Especially looking and searchingfor people who were former teachers,
and particularly if they wereformer international teachers
and looking for connections.
And then I would just reach out tothem and ask them if, well, they
had done, made their transitionand started building a network.
And the more.
People that, you know, then you startgetting connected to more of them and it,
(10:19):
it did start to grow and it, it grew a lotmore in the program 'cause other people
would be connected to somebody and thenI would connect to them and then I would
see people on their feet and I startedmaking comments and I actually really
grew a pretty good network of people.
But I didn't have, it was morewhen I was looking for jobs, I
didn't have people that I knew thatworked inside of a company, maybe
(10:43):
with a different kind of role thatcould help give me a, an internal
referral or, or that, that's when I.
It was more of a challenge.
It wasn't so much a challenge networkingand meeting people as it was that I did.
I didn't have INS any place.
And I remember one of the, you weretrying to show us during the accelerator
(11:03):
program that we all knew people, andyou were like, I want you to take out
your phone now, and I want you to lookat who you like Glass spoke to and.
Do you know what their's like, and peoplewere saying, oh, my cousins, or my, you
know, this, or my, and, and I'm like, oh,I spoke to an independent farmer in Laia.
Avery Smith (11:19):
Not the most data-centric role I would imagine.
Cynthia Clifford (11:22):
So that was where it was more challenging, was in
the job hunt part, not the meetingpeople online and connecting.
Avery Smith (11:30):
So how did you, how did you overcome the, the job hunt part?
Or, or how did you end up landingyour, your first, uh, data role?
Cynthia Clifford (11:38):
I looked for lots of kind of billboards and job sites that
weren't necessarily just LinkedIn, likeI think I'm the one who told you about
the tech Jobs for Good site, and Ifollowed lots of, I thought that my best
bet initially would probably be to getwith some sort of an education company
(12:00):
as a data analyst, so I was following.
Ed tech, blogs of various kindsand job postings through there,
and I applied to a lot of jobs.
Like I was more successful gettinginterviews when I applied to jobs
from some of these kind of less known.
Venues.
(12:20):
Um, I don't know if I ever reallygot an interview from anything I
applied for on LinkedIn, even if Iapplied on the company website, but
I'd found the listing on LinkedIn.
I, you know, I just, I didn'thave the corporate background.
I didn't have the connections, I didn'thave internal referrals, I had nothing.
So I had to essentially called, calleverything and always sent cover
(12:40):
letters that were very tailored.
To the job.
I always researched the company and Iprobably applied to fewer places per week
than many of the students in the program.
But I only applied to jobsthat I thought I was really
legitimately, pretty qual like that.
I, there was a reason whysomebody might look at me even
(13:00):
with my limited experience.
Avery Smith (13:03):
That makes a lot of sense.
I think most people are on LinkedInand only looking at at LinkedIn jobs,
which by the way, um, I don't know ifyou have seen this, oh, you have seen
this, but I have find data job.com
now and premium data jobs, which aretrying to pull, help people find jobs that
aren't necessarily listed on LinkedIn.
So now you could have used those jobsboards, but those didn't exist back then.
(13:23):
You're applying to jobs you thinkyou're a good fit for, you're looking
at job boards and job listingsthat maybe other people aren't.
And then.
You're, you're trying to stand out becauseyou're sending, you're sending cover
letters that are, that are quite tailored,and then is that how, how you and
Cynthia Clifford (13:37):
following companies that, that, that I, you know, ahead of
time and commenting on, on that company'sposting and those things as well.
Avery Smith (13:47):
Okay.
And how did you land your, your first jobwith, uh, with Impossible, right, which is
basically they make the, the vegan meat.
Cynthia Clifford (13:55):
I found that job on tech Jobs for Good, and I wrote a really
tailored cover letter because it wasvery clear from the job description
that cultural fit was really important.
I made sure that they knew that Itried impossible foods, that I, you
know, made ccad with the impossiblebeet for my vegetarian sons.
(14:19):
That I really knew what I was, that,that it's an important mission to
try to reduce some of the greenhousegases from animal production and
that I'm behind that mission, and Ithink that's why I got an interview.
Avery Smith (14:34):
That's really cool that you, you were really tying like,
you're like, Hey, I'm not just another,you're not just another company to me.
I'm not just another candidate to you.
I think this is a good culture fit.
We should also mention that like you,you live in Vermont, it's not like the
biggest corporates tech hub of the UnitedStates, so there's not a ton of data
(14:54):
jobs in Vermont, so you are also lookingfor remote, which, which obviously makes
things, uh, a bit more, more competitive.
Um, so you apply to this,this job as a remote job.
Do you remember what theinterview process was like at all?
Cynthia Clifford (15:06):
I had a screening with the the, with the recruiter who passed
me on to the hiring manager, and after Imet with her, I had four more interviews.
With different people in either theteam or a team I might interact with.
They were all half an hour.
(15:26):
There were two back to backand another two back to back.
So I met altogether with, besidesthe recruiter, with five people.
And I do know that.
They speeded the process up a littlebit because they asked me early on if I
was close to an offer or I got an offerfrom anybody else to let them know.
And I did get an offer from, and now from,uh, an agency in Vermont, a state agency.
(15:51):
So I was able to sort of parlay that.
I mean, and it was legitimate.
I mean, I did get that offer, but.
It was, I was able to sort of putpressure and move the process along.
Avery Smith (16:00):
Okay.
And do you remember theinterview being hard?
Like were there difficulttechnical questions?
Were they talking about stats or sequel?
Cynthia Clifford (16:08):
No.
All really kind of cultural fitand behavioral questions and I.
Avery Smith (16:12):
I, I find a lot of our students somehow get
internship or not internships.
I find a lot of our students getinterviews that are, are more behavioral
and, and less technical, which, whichI think is, is quite interesting.
Okay.
You're there for a bit.
And what type of tools, uh,are you using on the job?
Cynthia Clifford (16:30):
Mostly Google Sheets slash Excel and creating
templates of various kinds so thatI could take data that I would,
would access from outside databases.
I could take it and plunk it inand it would automatically update.
I had, I'd created a bunchof these sort of tools.
I had to prepare the weekly salesand share report, which went to
(16:53):
the executive leadership team.
That was all in PowerPoint, but Iwould have to pull pictures out of
the, these templates that I had made.
So I used sheets, I used PowerPoint,and, and then in the consumer
packaged goods industry, therewere a whole load of companies.
Numerator, IRI, Nielsen, MPD, theyall point of sales data, if you think
(17:15):
about it, is a massive data set.
And so they kind of aggregate allof this and they have their own
proprietary systems and you companiespay subscriptions to access this data.
And I would have to do the data pulls.
I really did pretty much all thedata pulls and supported the sales.
Team and created these reports andthe logic of these systems was quite
(17:41):
SQL based, but it wasn't SQL becausethere was an, you know, an overlay.
But I would have to, you know,pick this and group by this
and wasn't highly intuitive.
It was actually pretty hard tolearn some of these, and there were
like maybe three or four differentsystems I had to learn and one was
for food service and one was for.
(18:02):
Something else and one was just for Krogerand both was, and each was different.
Avery Smith (18:08):
I think that's important to to note because it's not like, like
in the accelerator that we can cover,you know, this, these types of tools.
And honestly like most jobs have somesort of proprietary data software or
industry specific data software that like.
Really you don't even knowexists until you're there.
And even if you did know exists, youprobably really couldn't access it, uh,
(18:30):
unless you work for like a corporation.
So it's, it's like that'sexists at every job I
Cynthia Clifford (18:34):
was interviewing.
They told me that I, part of thejob I would have to access IRI data.
So I looked up that thinking,all right, well, I'll go see
what this is like before.
And to be even to get, be evena researcher and get access
was over a thousand dollars.
So I was like, well, I guessI'm not gonna access that.
Avery Smith (18:54):
That's, that's how that goes.
Uh, that makes a lot of sense.
And you're wise for like, trying to lookit up beforehand and, and be prepared.
That was, that's really cool.
Okay, pause for a second.
Uh, I didn't really think through howwe wanna transition to your second job.
Uh.
I can say you're just there for a whileand then like you ended up getting
into, and they had had a reduction in
Cynthia Clifford (19:15):
force and they moved.
Um, and well that what, what theyactually did was they reclassified
all these jobs as hybrid honest truth.
They did that because theywanted people to quit, but Yes.
Um, because they had then ended upwith a big layoff shortly after that.
So I think we can just sortof say there was sort of.
They, they transitioned jobs andthere was a reduction in force.
Avery Smith (19:37):
Okay, so you're at Impossible Foods for a while.
And then they ended up kind ofreclassifying a lot of jobs to, instead
of being remotes, to be hybrid and, uh,their, their offices are not in Vermont.
And so you ended up, uh, not beingable to work at them and any further.
And then you had tofind, uh, a new data job.
How did you find the second data job?
Cynthia Clifford (19:57):
Well, I actually, this time I had several internal
referrals for things within theconsumer packaged goods industry.
So I was pursuing those.
I also was pursuing things I'dfound on LinkedIn or on your
job boards or, and I gone.
Actually the final round fourtimes and didn't get the job.
It was exhausting.
I mean, you know, done the project,done a panel presentation, like
(20:20):
all sorts of stuff for severaljobs and was feeling pretty down.
And I'm not, and somebody I knowfrom LinkedIn and I think from this
program, but, uh, okay, so someonefrom the program who I'd connected
with and we've had coffee chats with.
And continued to keep in contactwith, 'cause I always appreciate
(20:40):
her thoughtful comments on LinkedIn.
I had chatted with her, uh, becauseshe was looking for a new, a new role
or had just gone through the processof looking for a new role and I let
her know with the position I was in,and she actually said to me, I just
interviewed with a company and I.
They offered me a joband I'm not taking it.
(21:03):
And she said, not because it wasn'ta good job or a good company,
but she had personal reasons forwhy it wasn't the best fit for
her circumstances at the time.
And she said, if you'd like,I'll, I'll write to the hiring
manager and recommend you.
So even though she had turned this jobdown, she wrote to the hiring manager
(21:24):
and or to the, the recruiter and toldhim that she thought I would be a
great fit and I ended up meeting withhim without actually even applying.
And he then set me up to interview withthe hiring managers also before I'd ever
filled out an application on the site.
And.
Because I know that after, aftermeeting with the hiring managers, the
(21:48):
recruiters said, you know, we need tohave you fill out this application.
And she was great because she hadgiven me a little bit of heads up
about the sorts of questions they weregonna ask me in the interview as well.
So I was able to be very prepared.
The interview was.
With the hiring managers.
There were two of them.
It was a, it was a good interview.
They were both really thoughtful.
It was clear that theyhad a set of questions.
(22:10):
They were growing the team substantially.
A, a year before I joined, thisparticular team had maybe five or six,
maybe seven people, and now we're 20and they'd hired, I was one of the
last of this big explosion of hires.
The.
Questions were a mix of, I wouldn't sayhighly technical, but they did ask what
I, I mean, this is in the energy industry.
(22:32):
They asked, you know, what I knewabout how power was generated.
They asked if.
They asked questions about what wasthe most complex sorts of things
I've ever done with Excel, but theyalso asked behavioral questions.
Avery Smith (22:44):
Well, what's cool is, you know, you have been working as an
international teacher for, for a while,but you studied engineering in school
and you even had an engineering job, youknow, out of college for a little bit.
So I'm sure that like not only havingthis awesome, basically internal
reference to the hiring manager.
Also being like, Hey, look, Iunderstand engineering principles.
(23:06):
I think that probably sets youapart compared to most analysts.
Cynthia Clifford (23:09):
Oh, for sure.
Because when they asked me, you know, whatI knew about how energy was generated,
you know, you know, I was like, well, I.
I just spew off an answer like, well,there's lots and lots of ways of, you
know, getting, you know, convertingsort of potential energy to kinetic
energy and getting that turbine movingand getting, you know, and like I, you
know, I went on and thought it on, Ithink, and, and it's been really useful
(23:34):
in my work there to have that sortof understanding all of the analysts.
Take Workday courses all onthings like HVAC systems and,
and when I was an engineer, youwere chemical, I was mechanical
and thermodynamics was actually.
My best subject engineering jobI had when I was an engineer
(23:55):
was in energy conservation.
So even though it was quite awhile ago, those fundamentals are
in there and it's helpful now.
Avery Smith (24:03):
Very cool.
I wanted, I wanted to ask earlier, like,you know, even though you were a teacher.
Did you find that you had transfertransferable skills into analytics,
and obviously sounds like in thiscase your, your engineering background
stuff was, was transferable.
Were some of your teacherskills transferable as well?
Cynthia Clifford (24:20):
Oh, for sure.
I think that, I mean,in a variety of ways.
In my current role we are,we do a lot with statistics.
We look at the statistics of models,are these appropriate models?
Are is the, are the residualsnormally distributed?
That sort of thing.
And having taught higher level mathand AP statistics, I've been able
(24:42):
to actually contribute to my team.
By creating, we have team weeklyteam meetings that are team trainings
where people will present things andI presented on, oh, here's the Durbin
Watson statistic and auto correlation,and what does it really mean?
And used really simple examples that.
That aren't necessarily embedded inthe energy context, but are maybe
(25:04):
embedded in ice cream shops and beaches.
Everybody can understand and people havesaid that they've been really helpful.
I, knowing the statistics has certainlybeen transferable and, and, and math
modeling, I mean, understanding variables.
I, you know, I was the calculuslady, but other skills that all
teachers have are really transferable.
(25:25):
Teachers can learn new things.
When you're a teacher, you.
You get thrown into, you know, they'llbe like, oh, we have a new software that
we're gonna use for, you know, great.
And they'll bring one person in anddo a two hour point and click and
then they'll be like, off you go.
And teachers figure it out.
'cause they have to, I've been surprisedin the corporate world actually,
(25:46):
how much time they give you to.
Learn things.
'cause when you're a teacher,they don't give you that.
I think things like knowing how todo a presentation in, in Impossible
Foods, I had to make PowerPoints.
Like I actually, at one point, I, Ilooked at the PowerPoint and I was like,
you know, we just come out with thesenew company color branding and like,
(26:06):
is is there any chance I could likeredo the template for the PowerPoint?
So it's very cohesive, like, and what Imade then ended up saw it showing up in.
People much higher than me kind of takingmy templates and using them because
I, I know how to make a power one.
Avery Smith (26:26):
There's, there's all sorts of different ways that teachers
can, you know, transferable skills.
Even, even when you said earlier whenyou were talking about some of the
statistics and, you know, maybe not inenergy, but like in ice groups and stuff
like that, teachers are, are good atexplaining things and really like what
you're actually doing as a data analyst.
A lot of the time is just telling businesspeople or higher ups what's happening in
(26:50):
the business from a numbers perspective.
And so as a teacher, you're, you're,you've been trained to communicate
clearly, whether it's in a PowerPointor, or orally to say what's going on.
Uh, and like you said, also,teachers are fantastic students.
And like you said, at Impossible Foods,you had to learn this like proprietary
database system that like you couldn'treally learn on your own beforehand.
(27:10):
At your, your current company.
We haven't talked about it, butyou use this software called jump.
JMPI really like jump as well,but it's not like something that's
really, it's not super common.
It's, it's an awesome tool, but it's notsuper common and it's quite expensive.
Um, if you try to get like alicense on your own, it's gonna
cost you about $2,000 a year.
So it's not like something you, noone really learns, jump on their
(27:31):
own and then gets into a job.
You always learn jump.
On the job, and that's somethingthat teachers are gonna excel at.
They're gonna be great.
And, uh, to be honest, especially withhow AI's going right now, like we're
gonna have to keep learning new thingsyear after year after year as a data
analyst for the next two or three decades.
Cynthia Clifford (27:47):
Well, I use AI a lot of times in, in my role when
I'm, I'm doing some of the Excelbased work and I know I wanna maybe.
Pull something from this tab over to thisone and, and aggregate it by the week.
And, but when I, if I have blanks, Idon't want them to show up as zeros.
I want them to show up as nas, then I willput the appropriate information, describe
(28:13):
the situation and put that into ai.
'cause you, you can't obviously,you know, company spreadsheet, you
know, with chat GPT, but, but I willput in the relevant information and.
I ask for the, the code, and it's reallygood at giving me very succinct ways
to do some of the things I need to do.
Avery Smith (28:33):
I, I love that.
It's just AI is not replacing us.
It's just helping us work faster.
Um, I think that's really cool.
Has anything, has anything reallysurprised you as a data analyst?
Like maybe something you didn't realizethat, that the job would be like?
I.
Cynthia Clifford (28:47):
Well, I would say that my first role, I was surprised by
a lot of things, but a lot of that wasmore just the way that corporate works.
Coming from a teaching background, I,things are so different in teaching.
They want you to get something donefast and it might not be the most
perfect version of something, butif they say they want this, they,
(29:10):
well, they'll get something andthey'll get it when they need it.
I found that I had thatmentality and would be like,
well, did you proofread this?
Did you, I mean, like of course Iproofread it, but did you check this?
Did you run it by three or fourother people and get their feedback?
Did you do like for things thatwere supposed to be rushed and.
(29:32):
Could end up being, we're gonnaroll this new dashboard out,
it's gonna take two months.
And teaching it would be like, well,here it is, and like, you know, start
playing with it and figure out whatyou can, if there's problems, let me
know if there's problems, let me know.
Be an issue.
In teaching, it would be part ofthe process of how things work.
(29:52):
And it seems like in the corporateworld, it's all a lot slower.
But it has to be right.
Like they're not iteratingconstantly on the fly.
You're supposed to do all theseiterations and then say, here,
Avery Smith (30:06):
it's, it's, it's definitely a different world than, than teaching.
Uh, for sure.
What advice would you give to teacherswho want to become data analysts?
Cynthia Clifford (30:14):
The teachers are constantly evaluating and, and assessing
the situation and our problem solvingand data analysis really is about problem
solving and communicating the resultsof the problems you've solved or, you
know, every, like you said before,if, if, if they're sales data you're
trying to explain to an executive, not,you don't need to explain that the.
(30:38):
Sales went up, or sales went down.
That's a, like a concrete number,but you're trying to dig into
why and what other drivers arethere that made that happen?
Or in my current role, which are thevariables that are gonna best explain,
uh, best represent, allow us to createa model that will describe a company's.
(31:01):
And there might be tons of differentvariables, but we're trying to
come up with the ones like a reallysimple model that will still explain
really clearly and teachers do thesame thought process all the time.
Why is Joey not understanding?
This concept?
What is going on?
Is there a piece that's missing?
Is there like all that backthinking and the, Hmm, let me think.
(31:24):
Let me take a look.
Does he know how to do this?
Does he know how to do this?
Does he know how to do this?
Oh, and then he doesn'tknow how to do that.
So somewhere there's this connection thatJoey's not making or Johnny's not making.
Teachers do that all the time, andthey do it for rooms full of kids.
And they finish the day and they ruminateover what went well and what didn't
go well and why you're just applyingthat same skillset, that same sort
(31:48):
of thought process to a new context.
Avery Smith (31:52):
It's problem solving at the end of the day, and teachers have
always been good problem solvers.
Uh, Cindy, you're one of thebest problem solvers I know.
Uh, and I'm sure, uh, your currentcompany is super lucky to have
you, and I was lucky to have you.
As a student in, in the Accelerator.
Thanks so much for coming on theshow and, uh, sharing your story.
Cynthia Clifford (32:11):
No, it was my pleasure.
It was really good to catch up.
Avery, you were wonderfulto me and continue to be
Avery Smith (32:16):
good.
I'm glad I.
This is Cindy Clifford.
(00:01):
And Cindy was a teacher andeducator for over 25 years until
Cynthia Clifford (00:06):
I reached a real burnout stage with teaching and I knew
I needed to do something different.
Avery Smith (00:12):
And honestly, can you really blame her teaching is really,
really hard in the first place.
But Cindy was not only a teacher, shewas an international school teacher
and endured some pretty crazy thing.
Cynthia Clifford (00:23):
I was stuck in a military coup in Myanmar,
and then I went to Vietnam andI got stuck in Covid Lockdowns.
I spent a year teaching online withoutbeing able to leave my neighborhood.
Avery Smith (00:34):
Yeah, that's not fun at all.
Being a teacher is hard,but here's the truth.
Teachers make great data analysts.
In fact, most teachers are already kindof analyzing data one way or another.
Whether they realize it or not, teachers
Cynthia Clifford (00:48):
are constantly evaluating and assessing the situation
and our problem solving and dataanalysis really is about problem
solving and communicating the resultsof the problems you've solved.
Avery Smith (01:00):
In this episode, Cindy and I will explore her
data career story and what helpedher leave a career of 25 years.
Ultimately become a data analystat a company like Impossible Foods.
Thank you so much for subscribingto our show, and let's go ahead
and dive into this episode.
Alright, Cindy, you studied engineeringin college and then you had a 25 year
(01:20):
career in teaching all over the world.
What made you wanna become a data analyst?
Cynthia Clifford (01:26):
I wanted to become a data analyst because, well, partly,
and I know you've had other teachersthat in the program, I reached a real
burnout stage with teaching and I knewI needed to do something different,
and I'd known that for a while, but itreally reached a height, as you said,
I was teaching all over the world.
I was stuck in a military coup inMyanmar, and then I lost my job,
(01:50):
and then I went to Vietnam andI got stuck in Covid lockdowns.
I spent a year teaching online withoutbeing able to leave my neighborhood.
None of that was goodfor my mental health.
And I came back to the USafter that summer and I said,
alright, you gotta figure it out.
You absolutely have tofigure out what you wanna do.
And I spent the summerinformational interviewing.
(02:11):
I met.
Kind of everybody under the sunmade connections on LinkedIn,
asked them if I could ask abouttheir job and what they did.
I first thought I would want to do thekind of things that a lot of teachers
transition into, like, uh, instructionaldesign or learning and development
in a corporate environment, and.
Still realized that that wasn't thedirection I wanted to go, and I, you know,
(02:35):
I taught high school math and statistics.
I always, the math wasalways my favorite subject.
And data analysis started tomake, make a lot more sense.
I reached out to a, a formercolleague who's still a friend.
Who had already made that transitionand he's now a data scientist.
And he and I talked a lot aboutwhat I needed to learn and what
some of the ways to learn were.
(02:57):
And I decided I was gonna go for it.
So my last year of teaching overseas inVietnam, I spent weekends and evenings.
I started with the, the Google DataAnalytics certificate, and that confirmed
that I wanted to go in that direction.
But when I found you, I was really gladbecause I knew that I wasn't really, it
was like taking little quizzes and I'm,I'm a good student, I can do that, but
(03:21):
I knew that I wasn't really learning.
To do things in a way thatwas gonna help me find a job.
So
Avery Smith (03:27):
it makes a lot of sense 'cause my mom's a teacher.
Being a teacher, I mean, obviouslyyou're making a difference in kids'
lives and that's very meaningful andwe appreciate all of our teachers.
But being a teacher kind of sucksa lot of the time for many reasons.
Like you said, long hours, lowpay, and it can be just like.
Very stressful and, andfatiguing, so it makes sense.
You, you found somethingin, in data analytics.
(03:48):
You're like, okay, I'm good atmath, I'm good at statistics.
Let's do, let's do this and find alittle bit more of a calmer career.
Start off with the Google search.
I had forgotten about that and I.
And I like what you said, it would likeconfirm that like, okay, this is something
I wanna do moving forward, but didn'tlike, feel like it prepared you for a job.
Do you remember, I, this isgoing off script here, but do
you remember how you found me?
(04:08):
Like this was, this was a while now'cause you've been in your, in your
career now for what, almost two years?
I think so.
Yeah.
A
Cynthia Clifford (04:15):
hundred percent no.
But I know that I had startednetworking on LinkedIn and
reaching out to various people andmaking connections and comments.
None of it's supernatural to me,but I was already doing that and.
Following people and finding peoplewho had made the transition to data
who were formerly teachers, andsomewhere or other I came across your.
(04:41):
One of those come and listen tothe, my program, you know, talks
that you were running, what youwere saying made a lot of sense.
You know, I am kind of cheap and I waslike, Hmm, is this like legitimate or is
this, you know, one of these 'cause somany sort of scammy things on LinkedIn.
(05:02):
But I somehow, I trustedand I'm glad I did.
Avery Smith (05:06):
Good.
I'm, I'm glad you did as well.
Like you said, you kind of spent,uh, that last year of teaching
ramping up to, for this transition.
And I remember, I remember seeingyour, your comments in the community
late nights, I guess for, for meor or I, and for you, because, uh,
of the time difference, we usuallyhave live calls like at 7:00 PM
Eastern Time and for a while I,where were you and what time was it?
(05:28):
'cause you came to alot of our live calls.
Cynthia Clifford (05:29):
I wasn't able to go to a lot of those.
I was in Vietnam and it was like.
Seven in the morning for me, butI was already on my way to work.
Avery Smith (05:38):
I, I remember you coming to a couple in, in the mornings,
um, and you might be, well that's
Cynthia Clifford (05:43):
to then after daylight savings or something.
Ah, then it became six in the morningand I could go for an hour or for 50
minutes of it, and then I had to leave.
Avery Smith (05:52):
Perfect.
You were very dedicated and you,you did, uh, a lot of good research.
Were you nervous to makethis transition though?
Because you had been teaching forover 25 years where you're like, can
I really just reinvent myself again?
Cynthia Clifford (06:03):
I was definitely nervous, but I was also fairly feeling
fairly, like I just couldn't go onteaching and I had decided I wanted
to move back to the US and I did notwant to be a teacher in the US 'cause
I thought that would've even beenworse than being a teacher overseas.
Being a teacher overseas had beenreally good for a long time until it,
(06:24):
it wasn't, I didn't know exactly howlong it was gonna take you to find
a job, but I had saved up transitionand felt like I had a bit of a buffer
that if it also felt like, 'cause Iwas already older, like it was sort
of like, well, it's not now when like.
Like, I, I have to do it.
Like, so
Avery Smith (06:43):
I love that attitude though, because I feel like a lot of
people would just be like, ah, too late.
You know?
Um, but like, life's long andyou're also a very healthy person.
We've talked in the past, uh, youknow, about, uh, you try to, try to eat
healthy, try to exercise, stuff like that.
I.
Like life's long.
Like we have an opportunity, you know, we,we have to work, we have to go to work.
It's a big part of our lives.
(07:03):
Like, you know, you're spendingprobably like around eight hours
a day working everyone, right?
And you want to be doingsomething you enjoy.
You don't wanna be miserable.
Like if you're miserable now, like in1, 2, 5, 10 years, like, what's going
to change if you don't make a change?
And, and even if like the besttime to plant a tree was 10
years ago, the next best time.
Is today.
(07:24):
So I just wanna commend you forbeing brave, because I think a lot
of people wouldn't be brave andbe like, ah, oh, well I, I tried.
Cynthia Clifford (07:31):
Yeah.
No, I, I, but I, I am, I think in a lotof things, I have that attitude that
it's never too late to try new things.
I mean, I learned to cross countryski this year and working from home
in, in a cold climate like Vermont, I.
Spend too much time indoors in the winter.
So I decided this year that Iwas gonna learn to do a pull up
(07:51):
and put a pull-up bar outside myright where my office door is.
And every time I leave the room and tocome back, I have to practice a pull up.
I can now do a pull up.
Like, it's never too late to, to just try.
Like, otherwise you might as well, likeyou said, just curl up and it's done.
Avery Smith (08:09):
Be miserable.
For those of you, uh, for everyonelistening, you can definitely
tell what type of student, uh,Cindy is because she is ferocious.
Uh, you know, she's, she's willingto do, she's dedicated, she's, um,
consistent where she's like, even ifit's just one pull up, you know, I'm
just gonna try to do that one pull up.
Or if it's just a half, I'mgonna do the half pull up.
And that's how she was as a studentinside the accelerator program as well.
(08:31):
And I'll have to say, you kind of hadto be, because you were transitioning
from obviously not a tech field,like teaching is not a tech field.
And I'd almost argue that beingin education is almost like
a non-corporate field, right?
Like jobs aren't the same in the educationworld as they are in other industries.
Just because like it's,things are just different.
Like LinkedIn's not a thing and youget a lot of jobs from your district
(08:54):
or this and that, or like you're.
I don't know who, you know, yourprincipal or whatever, plus like you
weren't even in the us you hadn't evenbeen really in the US for a decade.
And so, you know, you joinmy program, you're like great
Avery's, SPN method I'm in.
And like the third part of the program,33% of the program is networking.
You're like, uh, I'm a teacher who'sbeen living overseas for a decade.
(09:16):
My network is, uh,maybe not the best ever.
So I just, I just wanna give youlike some credit for one being like
ferocious and battling through that.
'cause once again, a lot ofpeople I think, would use
that as an excuse and give up.
But like how did you network withlike this education and international
background that really maybewasn't super helpful for you?
Cynthia Clifford (09:35):
Well, I had actually found a program before
I found yours, which is how Istarted getting into LinkedIn.
I.
That program has is somethingthat helps teachers transition out
of teaching and there's a bunchof lessons including networking.
And I had been taking actionon that before I met you.
I was joining data groups and I.
(09:58):
Especially looking and searchingfor people who were former teachers,
and particularly if they wereformer international teachers
and looking for connections.
And then I would just reach out tothem and ask them if, well, they
had done, made their transitionand started building a network.
And the more.
People that, you know, then you startgetting connected to more of them and it,
(10:19):
it did start to grow and it, it grew a lotmore in the program 'cause other people
would be connected to somebody and thenI would connect to them and then I would
see people on their feet and I startedmaking comments and I actually really
grew a pretty good network of people.
But I didn't have, it was morewhen I was looking for jobs, I
didn't have people that I knew thatworked inside of a company, maybe
(10:43):
with a different kind of role thatcould help give me a, an internal
referral or, or that, that's when I.
It was more of a challenge.
It wasn't so much a challenge networkingand meeting people as it was that I did.
I didn't have INS any place.
And I remember one of the, you weretrying to show us during the accelerator
(11:03):
program that we all knew people, andyou were like, I want you to take out
your phone now, and I want you to lookat who you like Glass spoke to and.
Do you know what their's like, and peoplewere saying, oh, my cousins, or my, you
know, this, or my, and, and I'm like, oh,I spoke to an independent farmer in Laia.
Avery Smith (11:19):
Not the most data-centric role I would imagine.
Cynthia Clifford (11:22):
So that was where it was more challenging, was in
the job hunt part, not the meetingpeople online and connecting.
Avery Smith (11:30):
So how did you, how did you overcome the, the job hunt part?
Or, or how did you end up landingyour, your first, uh, data role?
Cynthia Clifford (11:38):
I looked for lots of kind of billboards and job sites that
weren't necessarily just LinkedIn, likeI think I'm the one who told you about
the tech Jobs for Good site, and Ifollowed lots of, I thought that my best
bet initially would probably be to getwith some sort of an education company
(12:00):
as a data analyst, so I was following.
Ed tech, blogs of various kindsand job postings through there,
and I applied to a lot of jobs.
Like I was more successful gettinginterviews when I applied to jobs
from some of these kind of less known.
Venues.
(12:20):
Um, I don't know if I ever reallygot an interview from anything I
applied for on LinkedIn, even if Iapplied on the company website, but
I'd found the listing on LinkedIn.
I, you know, I just, I didn'thave the corporate background.
I didn't have the connections, I didn'thave internal referrals, I had nothing.
So I had to essentially called, calleverything and always sent cover
(12:40):
letters that were very tailored.
To the job.
I always researched the company and Iprobably applied to fewer places per week
than many of the students in the program.
But I only applied to jobsthat I thought I was really
legitimately, pretty qual like that.
I, there was a reason whysomebody might look at me even
(13:00):
with my limited experience.
Avery Smith (13:03):
That makes a lot of sense.
I think most people are on LinkedInand only looking at at LinkedIn jobs,
which by the way, um, I don't know ifyou have seen this, oh, you have seen
this, but I have find data job.com
now and premium data jobs, which aretrying to pull, help people find jobs that
aren't necessarily listed on LinkedIn.
So now you could have used those jobsboards, but those didn't exist back then.
(13:23):
You're applying to jobs you thinkyou're a good fit for, you're looking
at job boards and job listingsthat maybe other people aren't.
And then.
You're, you're trying to stand out becauseyou're sending, you're sending cover
letters that are, that are quite tailored,and then is that how, how you and
Cynthia Clifford (13:37):
following companies that, that, that I, you know, ahead of
time and commenting on, on that company'sposting and those things as well.
Avery Smith (13:47):
Okay.
And how did you land your, your first jobwith, uh, with Impossible, right, which is
basically they make the, the vegan meat.
Cynthia Clifford (13:55):
I found that job on tech Jobs for Good, and I wrote a really
tailored cover letter because it wasvery clear from the job description
that cultural fit was really important.
I made sure that they knew that Itried impossible foods, that I, you
know, made ccad with the impossiblebeet for my vegetarian sons.
(14:19):
That I really knew what I was, that,that it's an important mission to
try to reduce some of the greenhousegases from animal production and
that I'm behind that mission, and Ithink that's why I got an interview.
Avery Smith (14:34):
That's really cool that you, you were really tying like,
you're like, Hey, I'm not just another,you're not just another company to me.
I'm not just another candidate to you.
I think this is a good culture fit.
We should also mention that like you,you live in Vermont, it's not like the
biggest corporates tech hub of the UnitedStates, so there's not a ton of data
(14:54):
jobs in Vermont, so you are also lookingfor remote, which, which obviously makes
things, uh, a bit more, more competitive.
Um, so you apply to this,this job as a remote job.
Do you remember what theinterview process was like at all?
Cynthia Clifford (15:06):
I had a screening with the the, with the recruiter who passed
me on to the hiring manager, and after Imet with her, I had four more interviews.
With different people in either theteam or a team I might interact with.
They were all half an hour.
(15:26):
There were two back to backand another two back to back.
So I met altogether with, besidesthe recruiter, with five people.
And I do know that.
They speeded the process up a littlebit because they asked me early on if I
was close to an offer or I got an offerfrom anybody else to let them know.
And I did get an offer from, and now from,uh, an agency in Vermont, a state agency.
(15:51):
So I was able to sort of parlay that.
I mean, and it was legitimate.
I mean, I did get that offer, but.
It was, I was able to sort of putpressure and move the process along.
Avery Smith (16:00):
Okay.
And do you remember theinterview being hard?
Like were there difficulttechnical questions?
Were they talking about stats or sequel?
Cynthia Clifford (16:08):
No.
All really kind of cultural fitand behavioral questions and I.
Avery Smith (16:12):
I, I find a lot of our students somehow get
internship or not internships.
I find a lot of our students getinterviews that are, are more behavioral
and, and less technical, which, whichI think is, is quite interesting.
Okay.
You're there for a bit.
And what type of tools, uh,are you using on the job?
Cynthia Clifford (16:30):
Mostly Google Sheets slash Excel and creating
templates of various kinds so thatI could take data that I would,
would access from outside databases.
I could take it and plunk it inand it would automatically update.
I had, I'd created a bunchof these sort of tools.
I had to prepare the weekly salesand share report, which went to
(16:53):
the executive leadership team.
That was all in PowerPoint, but Iwould have to pull pictures out of
the, these templates that I had made.
So I used sheets, I used PowerPoint,and, and then in the consumer
packaged goods industry, therewere a whole load of companies.
Numerator, IRI, Nielsen, MPD, theyall point of sales data, if you think
(17:15):
about it, is a massive data set.
And so they kind of aggregate allof this and they have their own
proprietary systems and you companiespay subscriptions to access this data.
And I would have to do the data pulls.
I really did pretty much all thedata pulls and supported the sales.
Team and created these reports andthe logic of these systems was quite
(17:41):
SQL based, but it wasn't SQL becausethere was an, you know, an overlay.
But I would have to, you know,pick this and group by this
and wasn't highly intuitive.
It was actually pretty hard tolearn some of these, and there were
like maybe three or four differentsystems I had to learn and one was
for food service and one was for.
(18:02):
Something else and one was just for Krogerand both was, and each was different.
Avery Smith (18:08):
I think that's important to to note because it's not like, like
in the accelerator that we can cover,you know, this, these types of tools.
And honestly like most jobs have somesort of proprietary data software or
industry specific data software that like.
Really you don't even knowexists until you're there.
And even if you did know exists, youprobably really couldn't access it, uh,
(18:30):
unless you work for like a corporation.
So it's, it's like that'sexists at every job I
Cynthia Clifford (18:34):
was interviewing.
They told me that I, part of thejob I would have to access IRI data.
So I looked up that thinking,all right, well, I'll go see
what this is like before.
And to be even to get, be evena researcher and get access
was over a thousand dollars.
So I was like, well, I guessI'm not gonna access that.
Avery Smith (18:54):
That's, that's how that goes.
Uh, that makes a lot of sense.
And you're wise for like, trying to lookit up beforehand and, and be prepared.
That was, that's really cool.
Okay, pause for a second.
Uh, I didn't really think through howwe wanna transition to your second job.
Uh.
I can say you're just there for a whileand then like you ended up getting
into, and they had had a reduction in
Cynthia Clifford (19:15):
force and they moved.
Um, and well that what, what theyactually did was they reclassified
all these jobs as hybrid honest truth.
They did that because theywanted people to quit, but Yes.
Um, because they had then ended upwith a big layoff shortly after that.
So I think we can just sortof say there was sort of.
They, they transitioned jobs andthere was a reduction in force.
Avery Smith (19:37):
Okay, so you're at Impossible Foods for a while.
And then they ended up kind ofreclassifying a lot of jobs to, instead
of being remotes, to be hybrid and, uh,their, their offices are not in Vermont.
And so you ended up, uh, not beingable to work at them and any further.
And then you had tofind, uh, a new data job.
How did you find the second data job?
Cynthia Clifford (19:57):
Well, I actually, this time I had several internal
referrals for things within theconsumer packaged goods industry.
So I was pursuing those.
I also was pursuing things I'dfound on LinkedIn or on your
job boards or, and I gone.
Actually the final round fourtimes and didn't get the job.
It was exhausting.
I mean, you know, done the project,done a panel presentation, like
(20:20):
all sorts of stuff for severaljobs and was feeling pretty down.
And I'm not, and somebody I knowfrom LinkedIn and I think from this
program, but, uh, okay, so someonefrom the program who I'd connected
with and we've had coffee chats with.
And continued to keep in contactwith, 'cause I always appreciate
(20:40):
her thoughtful comments on LinkedIn.
I had chatted with her, uh, becauseshe was looking for a new, a new role
or had just gone through the processof looking for a new role and I let
her know with the position I was in,and she actually said to me, I just
interviewed with a company and I.
They offered me a joband I'm not taking it.
(21:03):
And she said, not because it wasn'ta good job or a good company,
but she had personal reasons forwhy it wasn't the best fit for
her circumstances at the time.
And she said, if you'd like,I'll, I'll write to the hiring
manager and recommend you.
So even though she had turned this jobdown, she wrote to the hiring manager
(21:24):
and or to the, the recruiter and toldhim that she thought I would be a
great fit and I ended up meeting withhim without actually even applying.
And he then set me up to interview withthe hiring managers also before I'd ever
filled out an application on the site.
And.
Because I know that after, aftermeeting with the hiring managers, the
(21:48):
recruiters said, you know, we need tohave you fill out this application.
And she was great because she hadgiven me a little bit of heads up
about the sorts of questions they weregonna ask me in the interview as well.
So I was able to be very prepared.
The interview was.
With the hiring managers.
There were two of them.
It was a, it was a good interview.
They were both really thoughtful.
It was clear that theyhad a set of questions.
(22:10):
They were growing the team substantially.
A, a year before I joined, thisparticular team had maybe five or six,
maybe seven people, and now we're 20and they'd hired, I was one of the
last of this big explosion of hires.
The.
Questions were a mix of, I wouldn't sayhighly technical, but they did ask what
I, I mean, this is in the energy industry.
(22:32):
They asked, you know, what I knewabout how power was generated.
They asked if.
They asked questions about what wasthe most complex sorts of things
I've ever done with Excel, but theyalso asked behavioral questions.
Avery Smith (22:44):
Well, what's cool is, you know, you have been working as an
international teacher for, for a while,but you studied engineering in school
and you even had an engineering job, youknow, out of college for a little bit.
So I'm sure that like not only havingthis awesome, basically internal
reference to the hiring manager.
Also being like, Hey, look, Iunderstand engineering principles.
(23:06):
I think that probably sets youapart compared to most analysts.
Cynthia Clifford (23:09):
Oh, for sure.
Because when they asked me, you know, whatI knew about how energy was generated,
you know, you know, I was like, well, I.
I just spew off an answer like, well,there's lots and lots of ways of, you
know, getting, you know, convertingsort of potential energy to kinetic
energy and getting that turbine movingand getting, you know, and like I, you
know, I went on and thought it on, Ithink, and, and it's been really useful
(23:34):
in my work there to have that sortof understanding all of the analysts.
Take Workday courses all onthings like HVAC systems and,
and when I was an engineer, youwere chemical, I was mechanical
and thermodynamics was actually.
My best subject engineering jobI had when I was an engineer
(23:55):
was in energy conservation.
So even though it was quite awhile ago, those fundamentals are
in there and it's helpful now.
Avery Smith (24:03):
Very cool.
I wanted, I wanted to ask earlier, like,you know, even though you were a teacher.
Did you find that you had transfertransferable skills into analytics,
and obviously sounds like in thiscase your, your engineering background
stuff was, was transferable.
Were some of your teacherskills transferable as well?
Cynthia Clifford (24:20):
Oh, for sure.
I think that, I mean,in a variety of ways.
In my current role we are,we do a lot with statistics.
We look at the statistics of models,are these appropriate models?
Are is the, are the residualsnormally distributed?
That sort of thing.
And having taught higher level mathand AP statistics, I've been able
(24:42):
to actually contribute to my team.
By creating, we have team weeklyteam meetings that are team trainings
where people will present things andI presented on, oh, here's the Durbin
Watson statistic and auto correlation,and what does it really mean?
And used really simple examples that.
That aren't necessarily embedded inthe energy context, but are maybe
(25:04):
embedded in ice cream shops and beaches.
Everybody can understand and people havesaid that they've been really helpful.
I, knowing the statistics has certainlybeen transferable and, and, and math
modeling, I mean, understanding variables.
I, you know, I was the calculuslady, but other skills that all
teachers have are really transferable.
(25:25):
Teachers can learn new things.
When you're a teacher, you.
You get thrown into, you know, they'llbe like, oh, we have a new software that
we're gonna use for, you know, great.
And they'll bring one person in anddo a two hour point and click and
then they'll be like, off you go.
And teachers figure it out.
'cause they have to, I've been surprisedin the corporate world actually,
(25:46):
how much time they give you to.
Learn things.
'cause when you're a teacher,they don't give you that.
I think things like knowing how todo a presentation in, in Impossible
Foods, I had to make PowerPoints.
Like I actually, at one point, I, Ilooked at the PowerPoint and I was like,
you know, we just come out with thesenew company color branding and like,
(26:06):
is is there any chance I could likeredo the template for the PowerPoint?
So it's very cohesive, like, and what Imade then ended up saw it showing up in.
People much higher than me kind of takingmy templates and using them because
I, I know how to make a power one.
Avery Smith (26:26):
There's, there's all sorts of different ways that teachers
can, you know, transferable skills.
Even, even when you said earlier whenyou were talking about some of the
statistics and, you know, maybe not inenergy, but like in ice groups and stuff
like that, teachers are, are good atexplaining things and really like what
you're actually doing as a data analyst.
A lot of the time is just telling businesspeople or higher ups what's happening in
(26:50):
the business from a numbers perspective.
And so as a teacher, you're, you're,you've been trained to communicate
clearly, whether it's in a PowerPointor, or orally to say what's going on.
Uh, and like you said, also,teachers are fantastic students.
And like you said, at Impossible Foods,you had to learn this like proprietary
database system that like you couldn'treally learn on your own beforehand.
(27:10):
At your, your current company.
We haven't talked about it, butyou use this software called jump.
JMPI really like jump as well,but it's not like something that's
really, it's not super common.
It's, it's an awesome tool, but it's notsuper common and it's quite expensive.
Um, if you try to get like alicense on your own, it's gonna
cost you about $2,000 a year.
So it's not like something you, noone really learns, jump on their
(27:31):
own and then gets into a job.
You always learn jump.
On the job, and that's somethingthat teachers are gonna excel at.
They're gonna be great.
And, uh, to be honest, especially withhow AI's going right now, like we're
gonna have to keep learning new thingsyear after year after year as a data
analyst for the next two or three decades.
Cynthia Clifford (27:47):
Well, I use AI a lot of times in, in my role when
I'm, I'm doing some of the Excelbased work and I know I wanna maybe.
Pull something from this tab over to thisone and, and aggregate it by the week.
And, but when I, if I have blanks, Idon't want them to show up as zeros.
I want them to show up as nas, then I willput the appropriate information, describe
(28:13):
the situation and put that into ai.
'cause you, you can't obviously,you know, company spreadsheet, you
know, with chat GPT, but, but I willput in the relevant information and.
I ask for the, the code, and it's reallygood at giving me very succinct ways
to do some of the things I need to do.
Avery Smith (28:33):
I, I love that.
It's just AI is not replacing us.
It's just helping us work faster.
Um, I think that's really cool.
Has anything, has anything reallysurprised you as a data analyst?
Like maybe something you didn't realizethat, that the job would be like?
I.
Cynthia Clifford (28:47):
Well, I would say that my first role, I was surprised by
a lot of things, but a lot of that wasmore just the way that corporate works.
Coming from a teaching background, I,things are so different in teaching.
They want you to get something donefast and it might not be the most
perfect version of something, butif they say they want this, they,
(29:10):
well, they'll get something andthey'll get it when they need it.
I found that I had thatmentality and would be like,
well, did you proofread this?
Did you, I mean, like of course Iproofread it, but did you check this?
Did you run it by three or fourother people and get their feedback?
Did you do like for things thatwere supposed to be rushed and.
(29:32):
Could end up being, we're gonnaroll this new dashboard out,
it's gonna take two months.
And teaching it would be like, well,here it is, and like, you know, start
playing with it and figure out whatyou can, if there's problems, let me
know if there's problems, let me know.
Be an issue.
In teaching, it would be part ofthe process of how things work.
(29:52):
And it seems like in the corporateworld, it's all a lot slower.
But it has to be right.
Like they're not iteratingconstantly on the fly.
You're supposed to do all theseiterations and then say, here,
Avery Smith (30:06):
it's, it's, it's definitely a different world than, than teaching.
Uh, for sure.
What advice would you give to teacherswho want to become data analysts?
Cynthia Clifford (30:14):
The teachers are constantly evaluating and, and assessing
the situation and our problem solvingand data analysis really is about problem
solving and communicating the resultsof the problems you've solved or, you
know, every, like you said before,if, if, if they're sales data you're
trying to explain to an executive, not,you don't need to explain that the.
(30:38):
Sales went up, or sales went down.
That's a, like a concrete number,but you're trying to dig into
why and what other drivers arethere that made that happen?
Or in my current role, which are thevariables that are gonna best explain,
uh, best represent, allow us to createa model that will describe a company's.
(31:01):
And there might be tons of differentvariables, but we're trying to
come up with the ones like a reallysimple model that will still explain
really clearly and teachers do thesame thought process all the time.
Why is Joey not understanding?
This concept?
What is going on?
Is there a piece that's missing?
Is there like all that backthinking and the, Hmm, let me think.
(31:24):
Let me take a look.
Does he know how to do this?
Does he know how to do this?
Does he know how to do this?
Oh, and then he doesn'tknow how to do that.
So somewhere there's this connection thatJoey's not making or Johnny's not making.
Teachers do that all the time, andthey do it for rooms full of kids.
And they finish the day and they ruminateover what went well and what didn't
go well and why you're just applyingthat same skillset, that same sort
(31:48):
of thought process to a new context.
Avery Smith (31:52):
It's problem solving at the end of the day, and teachers have
always been good problem solvers.
Uh, Cindy, you're one of thebest problem solvers I know.
Uh, and I'm sure, uh, your currentcompany is super lucky to have
you, and I was lucky to have you.
As a student in, in the Accelerator.
Thanks so much for coming on theshow and, uh, sharing your story.
Cynthia Clifford (32:11):
No, it was my pleasure.
It was really good to catch up.
Avery, you were wonderfulto me and continue to be
Avery Smith (32:16):
good.
I'm glad I.
Popular Podcasts
Stuff You Should Know
If you've ever wanted to know about champagne, satanism, the Stonewall Uprising, chaos theory, LSD, El Nino, true crime and Rosa Parks, then look no further. Josh and Chuck have you covered.
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
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!