September 30, 2025 • 15 mins
Do you know how to negotiate a data scientist salary? In this episode, I cover data scientist compensation, my proven step-by-step data scientist salary negotiation strategies, and some common mistakes to avoid during a data scientist salary negotiation.
That way you have negotiation advice that is based on hundreds of salary negotiations and actually work for data scientists.
SALARY NEGOTIATION TOOLS MENTIONED
- Salary Negotiation Coaching: https://www.thesalarynegotiator.com/
- Salary Negotiation Courses: https://www.thesalarynegotiator.com/courses
- Salary Negotiation Scripts & Templates: https://www.thesalarynegotiator.com/salary-negotiation-templates
- How to Negotiate a Job Offer Guide: https://www.thesalarynegotiator.com/job-offer-negotiation-course
- How to Negotiate a Raise Guide: https://www.thesalarynegotiator.com/salary-negotiation-course
- Total Compensation Calculator: https://www.thesalarynegotiator.com/total-compensation-calculator
- How to Counter a Job Offer Guide: https://www.thesalarynegotiator.com/resource-center/counter-offer-salary
SALARY NEGOTIATION RESOURCES
- Data Scientist Salary Negotiation Guide: https://www.thesalarynegotiator.com/resource-center/how-to-negotiate-a-data-scientist-job-offer
- Meta Data Scientist Salary & Levels: https://www.thesalarynegotiator.com/meta-data-scientist-salary
- Video Guide
Like and subscribe!
CONNECT WITH ME
WHO AM I
I'm Brandon, the Founder and Lead Negotiator at TheSalaryNegotiator.com. As a former corporate negotiator, I now help employees increase their compensation. Through hundreds of salary negotiations, I've helped career professionals secure over $175 million in additional compensation. My expertise is backed by more than 150 five-star reviews from career professionals on Google and Trustpilot.
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
BrandonBramley (00:00):
Data scientists typically receive very
competitive compensation andbenefits, but how are you gonna
know if your job offer iscompetitive before you accept?
In this episode, my goal is tohelp you cover everything you
need to confidently not onlynavigate a data scientist salary
negotiation, but also ensurethat you're getting competitive
compensation in your new joboffer.
I'm first gonna cover thecompensation package structure
(00:20):
for most data scientist roles soyou know more about data
scientist-based salary, bonus,equity packages, and sign-up
bonuses.
That way you know exactly whatto inspect in an offer.
Then I'm gonna walk you throughmy five recommended steps for
negotiating a data scientist joboffer that are proven through
real data scientist salarynegotiations that I've led for
my clients.
That way you can filter outsome of the bad advice out there
(00:42):
and use salary negotiationstrategies that are actually
gonna work.
And I'll go ahead and close outthe episode by highlighting
multiple common mistakes youshould avoid in a data scientist
salary negotiation.
That way you don't risk theopportunity and you actually
secure competitive compensation.
So let's get into it.
Hey everyone, welcome back tothe channel.
If you're new here, my name isBrandon Bramley and I'm the
founder and lead negotiator atthesalarynegotiator.com (https://www.thesalarynegotiator.com/).
(01:04):
I provide professional salarynegotiation coaching,
courses (https://www.thesalarynegotiator.com/courses),and tools
(https://www.thesalarynegotiator.com/salary-negotiation-templates) tohelp professionals like you
navigate the negotiation processand secure a competitive comp.
I'm not just another careercoach or recruiter giving out
generic salary negotiationadvice.
There's already a lot of badadvice floating around online.
Instead, I personally ledhundreds of salary negotiations
across various roles, helping myclients secure hundreds of
(01:24):
millions more in compensation.
My background is in strategicnegotiations, and my goal is to
debunk some of the bad adviceout there and give you proven
negotiation strategies that areactually gonna help you earn
more.
So if you're a careerprofessional looking to earn
competitive pay, subscribe herefor actionable tips.
And when you're ready to takeyour negotiations to the next
level, visit me atthesalarynegotiator.com for
coaching,courses (https://www.thesalarynegotiator.com/job-offer-negotiation-course)
(01:44):
andtools (https://www.thesalarynegotiator.com/store/counteroffer-examples)
that are designed to help younegotiate competitive comp.
All right, so before we diveinto how to negotiate a data
scientist's salary, let's talkabout the compensation
components because it's reallyimportant to understand the
difference between your basesalary and your total
compensation as a datascientist (https://www.thesalarynegotiator.com/resource-center/how-to-negotiate-a-data-scientist-job-offer).
Too many data scientists focusonly on the base salary for a
role, but that's just one pieceof the puzzle when it comes to
(02:05):
pay.
So when you're considering anew company, you really need to
look at the whole picture, whichis your total monetary
take-home pay, also known asyour total compensation.
This is gonna include basesalary, bonuses, the value of
your vests in equity each year,and any sign-on bonuses.
Okay, so you're typically gonnafind those four core
compensation components in adata scientist offer package.
(02:26):
The first one you'll find isgonna be your data scientist
base salary.
This is pretty consistent.
This is nothing new.
It's the guaranteed pay thatyou're gonna see in every
paycheck, and it's really onlygonna change with your
promotions or merit increaseseach year since it's a set rate.
So I won't spend too much timethere.
But the second item you mightsee is an annual performance
bonus as a data scientist, whichis gonna be a percentage of
(02:46):
your base salary typically.
This is gonna range dependingon the data scientist level of
the role.
It can be based on yourpersonal or company performance,
and it's usually paid outannually, quarterly, or another
period.
But since it's a percentage,know that it can fluctuate.
Um, so while data scientists'bonus is typically tied to your
base salary, it's generally notnegotiable.
But the cool thing about thatis if you do negotiate a higher
(03:08):
base salary, your bonus willincrease along with it.
So keep that in mind as younavigate the negotiation.
The third comp component you'rehopefully gonna receive is
gonna be equity as a datascientist.
It usually comes in the form ofeither restricted Startup
units, RSUs, or employee stockoptions.
RSUs are gonna be actual stock,okay, which means you receive
shares in the company stockoutright once vested.
(03:30):
You're usually gonna see thatat a public company, whereas
stock options are gonna give youthe right to purchase a company
stock at a predetermined price.
For example, you pay anexercise price to go ahead and
exercise those options and thenyou get the shares, okay?
And you're gonna find thosemore like startups or non-public
companies.
Data scientist equity grantsare gonna usually come with a
stock vesting schedule, whichthis means you'll need to wait
(03:52):
for the equity to investaccording to that schedule
before you actually own theshares or options.
Most stock vesting periods aregonna be three to four years
with the equity vesting andincrements over that time.
And the stock vesting schedulemay be evenly distributed or
staggered.
So, for example, a MicrosoftRSU vesting schedule is a
four-year period with equalannual vesting amounts each
year.
Okay, so that means 25% you'llget each year.
(04:15):
Um, so 25% in year one, 25%invest in year two, 25% invest
in year three, and the final 25%invest in year four.
However, you'll find astaggered approach, say at
Amazon, where 5% best at the endof your first year, 15% at the
end of your second year, 40% ofthe end of year three, and then
the remaining 40% in year four.
So each company is gonna havetheir own specific vesting
(04:37):
schedule for data scientists,and you need to ask about this
when you get the offer.
One thing about equity is youdon't get the full value of the
equity up front, but luckily youdo share in the value
fluctuations over that period.
So if the stock price goes up,so does the value of your equity
as a data scientist.
The flip side is if the stockprice drops, so does your total
compensation and your equityvalue.
So there are risks when itcomes to equity.
(04:59):
And then if you do leave beforeyour equity fully vs, you are
going to forfeit the uninvestedportion of your equity.
So keep that in mind.
The final component you'lltypically see as a data
scientist is going to be a datascientist sign on bonus.
This is usually a one-time cashpayment, typically paid out
with your first paycheck or 30days after you start.
And it's usually designed tooffset loss incentives or equity
(05:19):
from your previous company.
But we've also found that youcan usually get them just as an
incentive to join as a newcompany.
All right.
Data scientist sign-on bonusesaren't always included in the
initial offer, so they do oftenrequire negotiation.
Um, but know that we've beenvery successful in securing them
for the data scientists that Iwork with.
So keep that in mind and justnote that it might take some
negotiating to secure one.
(05:40):
Um, and as for that, like othercompensation components you
might see is typically going tobe on the equity side, where
companies that do offer equityto data scientists might also
provide annual equity refreshersor stock refreshes, which are
additional equity grants eachyear.
However, these stock refreshersaren't always guaranteed and
they usually vary significantly.
So it's not an item I wouldtypically include in our total
(06:02):
compensation calculations, butyou should always ask about
these and see if they do existand see if you can get any
details from the recruiter soyou have a better idea of what
your future compensation mightlook like.
Now, these four main datascientists salary components,
your base salary, bonus, equity,and sign up bonus, are gonna
make up the total compensationas a data scientist at most
companies.
To help you visualize this, wehave a total compensation
(06:25):
calculator on our site.
It lets you input your basesalary, the bonus percentage,
the equity grant, and thesign-up bonus.
Then it's gonna show you yourestimated compensation over the
vesting period, both in totaland on an annual basis.
So you can find that free totalcompensation calculator at
thesalarynegotier.com.
And I'll also link it to it inthe episode notes below so you
can use this free tool.
But that way you have a way toactually look at your offer
(06:47):
package to see at what you'retruly making.
All right, now the fun part,right?
We've already covered the datascientist compensation structure
and how that works.
So now I want to discuss thedata scientist salary
negotiation steps.
These are the strategies thatI've used with many data
scientists to help themnegotiate their job offers, and
I'm gonna recommend you followto navigate your data scientist
salary(https://www.thesalarynegotiator.com/meta-data-scientist-salary) negotiation
once you have an offer in hand.
(07:08):
Now, once you have a datascientist job offer, the first
step to negotiating is to makesure you fully understand the
compensation components and thebenefits in your data scientist
offer package.
The biggest takeaway from thisis understanding the data
scientist total compensationbefore negotiating because that
way you know exactly how tovalue the data scientist offer
and what to negotiate.
So that includes the basesalary, the bonus, the equity,
(07:29):
and the sign on bonuses.
So don't skip that step.
The second step is what I calldoing your due diligence and
asking strategic questions.
This is where you're gonnareview the data scientist offer
letter and come back with a listof questions for the recruiter.
This not only helps you clarifyany questions you might have
about the offer, but it allowsyou to strategically ask
questions that are gonna buildyou salary negotiation leverage
(07:50):
with the recruiting team.
Okay, you're gonna go ahead andcall out items that might not
be as competitive compared toyour current company or your
competitors.
And if you need some ideas, Ihave a full list of strategic
questions on what to ask, bothon our templates page and in our
course.
That way you know how tostrategically draft these and
what questions to ask.
But don't skip this step, okay?
Even if you think youunderstand the offer, this step
(08:12):
is very important for buildingnegotiation leverage by showing
you're doing your research andyour due diligence before you
send a data scientistcounteroffer.
It also lets you secure anyfreebies on the items that might
be used as trade-offs later onin the salary negotiation.
So make sure you do it toprevent that later on.
Now, the third step, whichshould be big for data
scientists, is the compensationresearch, okay?
Where we're gonna want to findthe base salary and the total
(08:34):
compensation ranges for thespecific role, location, and
level at the new company.
So we can take a data-basedapproach.
All right, you're a datascientist, you should always be
leaning on data.
Don't skip this when younegotiate.
You can use various onlineresources to find this data,
just make sure you're averagingthe results across multiple
resources because with thisdata, it is publicly reported
(08:54):
and it might be higher comparedto what they might offer a new
hire because it includes equityappreciation, or whoever
uploaded it maybe didn'tunderstand what total
compensation is and missedcomponents.
So make sure you look atmultiple resources and you
average across those.
But if you need, you can useour compensation comparison
research tool that's gonnaactually help you pull in some
(09:14):
of that information.
So feel free to download that.
Or I walk through actually howto do the compensation research
in a lot more detail in ourcourse.
So both of those can help youout.
But essentially in this step,we're trying to find the base
salary and the totalcompensation range for a
specific role to find out wherethe initial offer sits, how much
more we should push for.
So once you have the datascientist compensation research
(09:35):
done and you've gotten theanswers to all your questions,
you're now ready to draft a datascientist counteroffer.
Okay, so this is where the funpart kicks off, and we take a
database approach to craft ourdata scientist counteroffer and
send it to the recruiting team.
We're gonna present the top endof the range you're targeting
based on your research and callout any items that weren't
competitive based on the duediligence questions.
My recommendation is to do thisby email.
(09:56):
And the reason for that isbecause it's gonna give the
recruiter everything they needto advocate for you and send
your points to the comp team.
Instead of hoping that if youcounter verbally, that they're
gonna take notes of it.
Plus, if you docounterverbally, the recruiters
negotiate offers every day.
They're gonna know where you'recoming and they're gonna cut
you off and steer you in adifferent direction.
So I recommend against that.
Um, and the final step, becausewe know that recruiters are
(10:19):
prepared in salary negotiationsas well as they negotiate offers
every day, is be prepared forpushback after you send a data
scientist counteroffer.
Okay, they're trained to pushback on you and they are gonna
give you pushback.
So we wanna overcome that tomake sure that your concerns in
the counteroffer make it back tothe decision makers.
So to do this, you essentiallywant to say that you understand
(10:40):
their concerns, but nicelyreiterate yours and ask them to
take it back to the team foranother look.
It's honestly gonna possiblytake a couple objections to
overcome before they agree totake back yet another look.
But nine times out of 10, ifyou do get them to take it back,
they will come back with abetter data scientist offer
package.
And if you need more details onhow to cover these or exactly
what to say to do thiseffectively, feel free to grab
(11:02):
my objection handling responseson the templates page or jump
into my course for me to talkthrough that more so you know
exactly how to encounter thisand how to overcome it.
So you don't come off asaggressive and you keep the tone
friendly and have a strategicapproach to navigate that
process.
Um, but as long as you do thatand you get them to take it back
from here, it's really just awaiting game.
They're either gonna come backwith a better offer that fits
(11:24):
your needs, or it's gonna belower than what you asked or not
move at all.
And at that point, you caneither see if you're ready to
accept or if you want to takesend another data scientist
counteroffer.
The only thing I want tohighlight is note that
negotiations aren't like whatyou'd see at like a car
dealership or maybe what youthought you saw online in the
past, is there's not a lot ofback and forth of arguing over
numbers.
(11:44):
Usually you don't want to sendmore than two counteroffers,
otherwise, you do risk comingoff as aggressive and
jeopardized relationship.
So make sure you take astrategic approach from the
beginning to hopefully get mostof the movement in the first
counter and then decide if it'sworth pressing again or not.
Okay, so we chatted through thedata scientist salary
negotiation steps, but there area lot of mistakes that pop up
(12:04):
that I see people do that I wantto call out before you
negotiate a data scientist'soffer letter.
The main item I recommendagainst is don't share your
salary expectations or yourcurrent pay with the recruiting
team.
This is usually only gonna workagainst you, right?
I get it.
You're a data scientist, you'rehopefully gonna have some of
these numbers in mind and youwant to share these, right?
But that's just gonna workagainst you.
And the risk there is if youthrow out a number that's lower
(12:26):
than what they could offer,there's more likelihood that
they'll give you a lesscompensation package than they
could have offered at the lowend of their pay range.
Or since most data scientistsroles are within tech companies,
if they find out thecompensation you're requesting
or you're currently making is inline with a lower level than
what you interviewed for,they're more than likely gonna
downlevel you and bring you inat that lower level.
So just don't do it.
(12:46):
And on the flip side, if youthink, hey, I'm gonna be
aggressive and I'm gonna throwout numbers that are higher just
to get a competitive package,be careful because they might be
like, hey, we can't afford thisdata scientist.
Let's go in a differentcandidate and stop the
recruiting in the interviews nowso we don't waste our time.
So it's not a good strategy andit can risk the opportunity.
And if you think about it, therecruiter knows exactly how much
(13:07):
they can pay for the datascientist role.
So you want to turn thatquestion back on them to learn
more about both the base salaryand the total compensation
ranges for the positions.
Then during the negotiation,you can do your own individual
research on both um the basesalary and the total
compensation to see if theranges they're sharing are
truthful or how much you shouldpush for once you have an offer
in hand.
Okay.
(13:28):
The next mistake I want you toavoid is make sure you're being
realistic about what you shouldask for in the data scientist
counteroffer.
Way too often do I seescientists ask for way too much
that doesn't make sense, right?
You're either gonna get laughedoff at or it's gonna come off
as aggressive.
In some cases, if you come offas too aggressive, you can get
the offer ascended.
So avoid that and always take adata-based approach as a data
(13:49):
scientist to make sure you'reasking for realistic
compensation they can provide.
Okay, because every company isgonna have set compensation bans
and they're only gonna paywithin those bands for the
specific role level.
So don't jeopardize the offerby coming off as too aggressive
and asking for unrealisticnumbers.
Just don't do it.
And finally, look, I understandthat negotiation might not be
(14:09):
the skill set you have that youtypically lean on as a data
scientist, but it's okay.
All right, you might feelnervous, but as long as you
follow proven strategies andkeep the negotiation
professional, there's no riskyou at risk the offer.
Okay, so if you do it right,you should secure a better data
scientist offer package beforestarting.
So have confidence in this, butjust make sure you're providing
(14:30):
and following proven strategiesat work.
And if you need it, get thesupport you need to negotiate a
data scientist offer package.
All right, team, that wraps upthis episode on data scientist
salary negotiation.
I hope my breakdown of datascientists' compensation
structure, our proven datascientist salary negotiation
tips and strategies, and thenegotiation mistakes to avoid as
a data scientist help you feelmore confident in these
(14:50):
discussions.
But honestly, if you're seriousabout getting the best possible
offer, I highly suggest youdon't go into the salary
negotiation alone.
So feel free to head over tothesalarynegotiator.com to
either work with me directly asyour salary negotiation coach or
check out my salary negotiationcourses, templates, and tools.
You can find all the links inthe episode notes below, but
those are all designed to helpyou navigate these conversations
(15:11):
and get competitive pay.
So please use them.
And honestly, if you found thisepisode helpful, make sure you
subscribe, leave me a comment,and share it with someone who
can use this advice in theircareer.
So thanks for tuning in andgood luck negotiating.
Data scientists typically receive very
competitive compensation andbenefits, but how are you gonna
know if your job offer iscompetitive before you accept?
In this episode, my goal is tohelp you cover everything you
need to confidently not onlynavigate a data scientist salary
negotiation, but also ensurethat you're getting competitive
compensation in your new joboffer.
I'm first gonna cover thecompensation package structure
(00:20):
for most data scientist roles soyou know more about data
scientist-based salary, bonus,equity packages, and sign-up
bonuses.
That way you know exactly whatto inspect in an offer.
Then I'm gonna walk you throughmy five recommended steps for
negotiating a data scientist joboffer that are proven through
real data scientist salarynegotiations that I've led for
my clients.
That way you can filter outsome of the bad advice out there
(00:42):
and use salary negotiationstrategies that are actually
gonna work.
And I'll go ahead and close outthe episode by highlighting
multiple common mistakes youshould avoid in a data scientist
salary negotiation.
That way you don't risk theopportunity and you actually
secure competitive compensation.
So let's get into it.
Hey everyone, welcome back tothe channel.
If you're new here, my name isBrandon Bramley and I'm the
founder and lead negotiator atthesalarynegotiator.com (https://www.thesalarynegotiator.com/).
(01:04):
I provide professional salarynegotiation coaching,
courses (https://www.thesalarynegotiator.com/courses),and tools
(https://www.thesalarynegotiator.com/salary-negotiation-templates) tohelp professionals like you
navigate the negotiation processand secure a competitive comp.
I'm not just another careercoach or recruiter giving out
generic salary negotiationadvice.
There's already a lot of badadvice floating around online.
Instead, I personally ledhundreds of salary negotiations
across various roles, helping myclients secure hundreds of
(01:24):
millions more in compensation.
My background is in strategicnegotiations, and my goal is to
debunk some of the bad adviceout there and give you proven
negotiation strategies that areactually gonna help you earn
more.
So if you're a careerprofessional looking to earn
competitive pay, subscribe herefor actionable tips.
And when you're ready to takeyour negotiations to the next
level, visit me atthesalarynegotiator.com for
coaching,courses (https://www.thesalarynegotiator.com/job-offer-negotiation-course)
(01:44):
andtools (https://www.thesalarynegotiator.com/store/counteroffer-examples)
that are designed to help younegotiate competitive comp.
All right, so before we diveinto how to negotiate a data
scientist's salary, let's talkabout the compensation
components because it's reallyimportant to understand the
difference between your basesalary and your total
compensation as a datascientist (https://www.thesalarynegotiator.com/resource-center/how-to-negotiate-a-data-scientist-job-offer).
Too many data scientists focusonly on the base salary for a
role, but that's just one pieceof the puzzle when it comes to
(02:05):
pay.
So when you're considering anew company, you really need to
look at the whole picture, whichis your total monetary
take-home pay, also known asyour total compensation.
This is gonna include basesalary, bonuses, the value of
your vests in equity each year,and any sign-on bonuses.
Okay, so you're typically gonnafind those four core
compensation components in adata scientist offer package.
(02:26):
The first one you'll find isgonna be your data scientist
base salary.
This is pretty consistent.
This is nothing new.
It's the guaranteed pay thatyou're gonna see in every
paycheck, and it's really onlygonna change with your
promotions or merit increaseseach year since it's a set rate.
So I won't spend too much timethere.
But the second item you mightsee is an annual performance
bonus as a data scientist, whichis gonna be a percentage of
(02:46):
your base salary typically.
This is gonna range dependingon the data scientist level of
the role.
It can be based on yourpersonal or company performance,
and it's usually paid outannually, quarterly, or another
period.
But since it's a percentage,know that it can fluctuate.
Um, so while data scientists'bonus is typically tied to your
base salary, it's generally notnegotiable.
But the cool thing about thatis if you do negotiate a higher
(03:08):
base salary, your bonus willincrease along with it.
So keep that in mind as younavigate the negotiation.
The third comp component you'rehopefully gonna receive is
gonna be equity as a datascientist.
It usually comes in the form ofeither restricted Startup
units, RSUs, or employee stockoptions.
RSUs are gonna be actual stock,okay, which means you receive
shares in the company stockoutright once vested.
(03:30):
You're usually gonna see thatat a public company, whereas
stock options are gonna give youthe right to purchase a company
stock at a predetermined price.
For example, you pay anexercise price to go ahead and
exercise those options and thenyou get the shares, okay?
And you're gonna find thosemore like startups or non-public
companies.
Data scientist equity grantsare gonna usually come with a
stock vesting schedule, whichthis means you'll need to wait
(03:52):
for the equity to investaccording to that schedule
before you actually own theshares or options.
Most stock vesting periods aregonna be three to four years
with the equity vesting andincrements over that time.
And the stock vesting schedulemay be evenly distributed or
staggered.
So, for example, a MicrosoftRSU vesting schedule is a
four-year period with equalannual vesting amounts each
year.
Okay, so that means 25% you'llget each year.
(04:15):
Um, so 25% in year one, 25%invest in year two, 25% invest
in year three, and the final 25%invest in year four.
However, you'll find astaggered approach, say at
Amazon, where 5% best at the endof your first year, 15% at the
end of your second year, 40% ofthe end of year three, and then
the remaining 40% in year four.
So each company is gonna havetheir own specific vesting
(04:37):
schedule for data scientists,and you need to ask about this
when you get the offer.
One thing about equity is youdon't get the full value of the
equity up front, but luckily youdo share in the value
fluctuations over that period.
So if the stock price goes up,so does the value of your equity
as a data scientist.
The flip side is if the stockprice drops, so does your total
compensation and your equityvalue.
So there are risks when itcomes to equity.
(04:59):
And then if you do leave beforeyour equity fully vs, you are
going to forfeit the uninvestedportion of your equity.
So keep that in mind.
The final component you'lltypically see as a data
scientist is going to be a datascientist sign on bonus.
This is usually a one-time cashpayment, typically paid out
with your first paycheck or 30days after you start.
And it's usually designed tooffset loss incentives or equity
(05:19):
from your previous company.
But we've also found that youcan usually get them just as an
incentive to join as a newcompany.
All right.
Data scientist sign-on bonusesaren't always included in the
initial offer, so they do oftenrequire negotiation.
Um, but know that we've beenvery successful in securing them
for the data scientists that Iwork with.
So keep that in mind and justnote that it might take some
negotiating to secure one.
(05:40):
Um, and as for that, like othercompensation components you
might see is typically going tobe on the equity side, where
companies that do offer equityto data scientists might also
provide annual equity refreshersor stock refreshes, which are
additional equity grants eachyear.
However, these stock refreshersaren't always guaranteed and
they usually vary significantly.
So it's not an item I wouldtypically include in our total
(06:02):
compensation calculations, butyou should always ask about
these and see if they do existand see if you can get any
details from the recruiter soyou have a better idea of what
your future compensation mightlook like.
Now, these four main datascientists salary components,
your base salary, bonus, equity,and sign up bonus, are gonna
make up the total compensationas a data scientist at most
companies.
To help you visualize this, wehave a total compensation
(06:25):
calculator on our site.
It lets you input your basesalary, the bonus percentage,
the equity grant, and thesign-up bonus.
Then it's gonna show you yourestimated compensation over the
vesting period, both in totaland on an annual basis.
So you can find that free totalcompensation calculator at
thesalarynegotier.com.
And I'll also link it to it inthe episode notes below so you
can use this free tool.
But that way you have a way toactually look at your offer
(06:47):
package to see at what you'retruly making.
All right, now the fun part,right?
We've already covered the datascientist compensation structure
and how that works.
So now I want to discuss thedata scientist salary
negotiation steps.
These are the strategies thatI've used with many data
scientists to help themnegotiate their job offers, and
I'm gonna recommend you followto navigate your data scientist
salary(https://www.thesalarynegotiator.com/meta-data-scientist-salary) negotiation
once you have an offer in hand.
(07:08):
Now, once you have a datascientist job offer, the first
step to negotiating is to makesure you fully understand the
compensation components and thebenefits in your data scientist
offer package.
The biggest takeaway from thisis understanding the data
scientist total compensationbefore negotiating because that
way you know exactly how tovalue the data scientist offer
and what to negotiate.
So that includes the basesalary, the bonus, the equity,
(07:29):
and the sign on bonuses.
So don't skip that step.
The second step is what I calldoing your due diligence and
asking strategic questions.
This is where you're gonnareview the data scientist offer
letter and come back with a listof questions for the recruiter.
This not only helps you clarifyany questions you might have
about the offer, but it allowsyou to strategically ask
questions that are gonna buildyou salary negotiation leverage
(07:50):
with the recruiting team.
Okay, you're gonna go ahead andcall out items that might not
be as competitive compared toyour current company or your
competitors.
And if you need some ideas, Ihave a full list of strategic
questions on what to ask, bothon our templates page and in our
course.
That way you know how tostrategically draft these and
what questions to ask.
But don't skip this step, okay?
Even if you think youunderstand the offer, this step
(08:12):
is very important for buildingnegotiation leverage by showing
you're doing your research andyour due diligence before you
send a data scientistcounteroffer.
It also lets you secure anyfreebies on the items that might
be used as trade-offs later onin the salary negotiation.
So make sure you do it toprevent that later on.
Now, the third step, whichshould be big for data
scientists, is the compensationresearch, okay?
Where we're gonna want to findthe base salary and the total
(08:34):
compensation ranges for thespecific role, location, and
level at the new company.
So we can take a data-basedapproach.
All right, you're a datascientist, you should always be
leaning on data.
Don't skip this when younegotiate.
You can use various onlineresources to find this data,
just make sure you're averagingthe results across multiple
resources because with thisdata, it is publicly reported
(08:54):
and it might be higher comparedto what they might offer a new
hire because it includes equityappreciation, or whoever
uploaded it maybe didn'tunderstand what total
compensation is and missedcomponents.
So make sure you look atmultiple resources and you
average across those.
But if you need, you can useour compensation comparison
research tool that's gonnaactually help you pull in some
(09:14):
of that information.
So feel free to download that.
Or I walk through actually howto do the compensation research
in a lot more detail in ourcourse.
So both of those can help youout.
But essentially in this step,we're trying to find the base
salary and the totalcompensation range for a
specific role to find out wherethe initial offer sits, how much
more we should push for.
So once you have the datascientist compensation research
(09:35):
done and you've gotten theanswers to all your questions,
you're now ready to draft a datascientist counteroffer.
Okay, so this is where the funpart kicks off, and we take a
database approach to craft ourdata scientist counteroffer and
send it to the recruiting team.
We're gonna present the top endof the range you're targeting
based on your research and callout any items that weren't
competitive based on the duediligence questions.
My recommendation is to do thisby email.
(09:56):
And the reason for that isbecause it's gonna give the
recruiter everything they needto advocate for you and send
your points to the comp team.
Instead of hoping that if youcounter verbally, that they're
gonna take notes of it.
Plus, if you docounterverbally, the recruiters
negotiate offers every day.
They're gonna know where you'recoming and they're gonna cut
you off and steer you in adifferent direction.
So I recommend against that.
Um, and the final step, becausewe know that recruiters are
(10:19):
prepared in salary negotiationsas well as they negotiate offers
every day, is be prepared forpushback after you send a data
scientist counteroffer.
Okay, they're trained to pushback on you and they are gonna
give you pushback.
So we wanna overcome that tomake sure that your concerns in
the counteroffer make it back tothe decision makers.
So to do this, you essentiallywant to say that you understand
(10:40):
their concerns, but nicelyreiterate yours and ask them to
take it back to the team foranother look.
It's honestly gonna possiblytake a couple objections to
overcome before they agree totake back yet another look.
But nine times out of 10, ifyou do get them to take it back,
they will come back with abetter data scientist offer
package.
And if you need more details onhow to cover these or exactly
what to say to do thiseffectively, feel free to grab
(11:02):
my objection handling responseson the templates page or jump
into my course for me to talkthrough that more so you know
exactly how to encounter thisand how to overcome it.
So you don't come off asaggressive and you keep the tone
friendly and have a strategicapproach to navigate that
process.
Um, but as long as you do thatand you get them to take it back
from here, it's really just awaiting game.
They're either gonna come backwith a better offer that fits
(11:24):
your needs, or it's gonna belower than what you asked or not
move at all.
And at that point, you caneither see if you're ready to
accept or if you want to takesend another data scientist
counteroffer.
The only thing I want tohighlight is note that
negotiations aren't like whatyou'd see at like a car
dealership or maybe what youthought you saw online in the
past, is there's not a lot ofback and forth of arguing over
numbers.
(11:44):
Usually you don't want to sendmore than two counteroffers,
otherwise, you do risk comingoff as aggressive and
jeopardized relationship.
So make sure you take astrategic approach from the
beginning to hopefully get mostof the movement in the first
counter and then decide if it'sworth pressing again or not.
Okay, so we chatted through thedata scientist salary
negotiation steps, but there area lot of mistakes that pop up
(12:04):
that I see people do that I wantto call out before you
negotiate a data scientist'soffer letter.
The main item I recommendagainst is don't share your
salary expectations or yourcurrent pay with the recruiting
team.
This is usually only gonna workagainst you, right?
I get it.
You're a data scientist, you'rehopefully gonna have some of
these numbers in mind and youwant to share these, right?
But that's just gonna workagainst you.
And the risk there is if youthrow out a number that's lower
(12:26):
than what they could offer,there's more likelihood that
they'll give you a lesscompensation package than they
could have offered at the lowend of their pay range.
Or since most data scientistsroles are within tech companies,
if they find out thecompensation you're requesting
or you're currently making is inline with a lower level than
what you interviewed for,they're more than likely gonna
downlevel you and bring you inat that lower level.
So just don't do it.
(12:46):
And on the flip side, if youthink, hey, I'm gonna be
aggressive and I'm gonna throwout numbers that are higher just
to get a competitive package,be careful because they might be
like, hey, we can't afford thisdata scientist.
Let's go in a differentcandidate and stop the
recruiting in the interviews nowso we don't waste our time.
So it's not a good strategy andit can risk the opportunity.
And if you think about it, therecruiter knows exactly how much
(13:07):
they can pay for the datascientist role.
So you want to turn thatquestion back on them to learn
more about both the base salaryand the total compensation
ranges for the positions.
Then during the negotiation,you can do your own individual
research on both um the basesalary and the total
compensation to see if theranges they're sharing are
truthful or how much you shouldpush for once you have an offer
in hand.
Okay.
(13:28):
The next mistake I want you toavoid is make sure you're being
realistic about what you shouldask for in the data scientist
counteroffer.
Way too often do I seescientists ask for way too much
that doesn't make sense, right?
You're either gonna get laughedoff at or it's gonna come off
as aggressive.
In some cases, if you come offas too aggressive, you can get
the offer ascended.
So avoid that and always take adata-based approach as a data
(13:49):
scientist to make sure you'reasking for realistic
compensation they can provide.
Okay, because every company isgonna have set compensation bans
and they're only gonna paywithin those bands for the
specific role level.
So don't jeopardize the offerby coming off as too aggressive
and asking for unrealisticnumbers.
Just don't do it.
And finally, look, I understandthat negotiation might not be
(14:09):
the skill set you have that youtypically lean on as a data
scientist, but it's okay.
All right, you might feelnervous, but as long as you
follow proven strategies andkeep the negotiation
professional, there's no riskyou at risk the offer.
Okay, so if you do it right,you should secure a better data
scientist offer package beforestarting.
So have confidence in this, butjust make sure you're providing
(14:30):
and following proven strategiesat work.
And if you need it, get thesupport you need to negotiate a
data scientist offer package.
All right, team, that wraps upthis episode on data scientist
salary negotiation.
I hope my breakdown of datascientists' compensation
structure, our proven datascientist salary negotiation
tips and strategies, and thenegotiation mistakes to avoid as
a data scientist help you feelmore confident in these
(14:50):
discussions.
But honestly, if you're seriousabout getting the best possible
offer, I highly suggest youdon't go into the salary
negotiation alone.
So feel free to head over tothesalarynegotiator.com to
either work with me directly asyour salary negotiation coach or
check out my salary negotiationcourses, templates, and tools.
You can find all the links inthe episode notes below, but
those are all designed to helpyou navigate these conversations
(15:11):
and get competitive pay.
So please use them.
And honestly, if you found thisepisode helpful, make sure you
subscribe, leave me a comment,and share it with someone who
can use this advice in theircareer.
So thanks for tuning in andgood luck negotiating.
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