Data Scientist Salary Negotiation - How to Negotiate a Data Scientist Salary

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Data scientists typically receive very competitive compensation and benefits, but how are you gonna know if your job offer is competitive before you accept?
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In this episode, my goal is to help you cover everything you need to confidently not only navigate a data scientist salary negotiation, but also ensure that you're getting competitive compensation in your new job offer.
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I'm first gonna cover the compensation package structure for most data scientist roles so you know more about data scientist-based salary, bonus, equity packages, and sign-up bonuses.
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That way you know exactly what to inspect in an offer.
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Then I'm gonna walk you through my five recommended steps for negotiating a data scientist job offer that are proven through real data scientist salary negotiations that I've led for my clients.
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That way you can filter out some of the bad advice out there and use salary negotiation strategies that are actually gonna work.
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And I'll go ahead and close out the episode by highlighting multiple common mistakes you should avoid in a data scientist salary negotiation.
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That way you don't risk the opportunity and you actually secure competitive compensation.
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So let's get into it.
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Hey everyone, welcome back to the channel.
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If you're new here, my name is Brandon Bramley and I'm the founder and lead negotiator at thesalarynegotiator.com (https://www.thesalarynegotiator.com/).
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I provide professional salary negotiation coaching, courses (https://www.thesalarynegotiator.com/courses), and tools (https://www.thesalarynegotiator.com/salary-negotiation-templates) to help professionals like you navigate the negotiation process and secure a competitive comp.
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I'm not just another career coach or recruiter giving out generic salary negotiation advice.
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There's already a lot of bad advice floating around online.
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Instead, I personally led hundreds of salary negotiations across various roles, helping my clients secure hundreds of millions more in compensation.
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My background is in strategic negotiations, and my goal is to debunk some of the bad advice out there and give you proven negotiation strategies that are actually gonna help you earn more.
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So if you're a career professional looking to earn competitive pay, subscribe here for actionable tips.
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And when you're ready to take your negotiations to the next level, visit me at thesalarynegotiator.com for coaching, courses (https://www.thesalarynegotiator.com/job-offer-negotiation-course) and tools (https://www.thesalarynegotiator.com/store/counteroffer-examples) that are designed to help you negotiate competitive comp.
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All right, so before we dive into how to negotiate a data scientist's salary, let's talk about the compensation components because it's really important to understand the difference between your base salary and your total compensation as a data scientist (https://www.thesalarynegotiator.com/resource-center/how-to-negotiate-a-data-scientist-job-offer).
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Too many data scientists focus only on the base salary for a role, but that's just one piece of the puzzle when it comes to pay.
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So when you're considering a new company, you really need to look at the whole picture, which is your total monetary take-home pay, also known as your total compensation.
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This is gonna include base salary, bonuses, the value of your vests in equity each year, and any sign-on bonuses.
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Okay, so you're typically gonna find those four core compensation components in a data scientist offer package.
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The first one you'll find is gonna be your data scientist base salary.
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This is pretty consistent.
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This is nothing new.
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It's the guaranteed pay that you're gonna see in every paycheck, and it's really only gonna change with your promotions or merit increases each year since it's a set rate.
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So I won't spend too much time there.
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But the second item you might see is an annual performance bonus as a data scientist, which is gonna be a percentage of your base salary typically.
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This is gonna range depending on the data scientist level of the role.
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It can be based on your personal or company performance, and it's usually paid out annually, quarterly, or another period.
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But since it's a percentage, know that it can fluctuate.
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Um, so while data scientists' bonus is typically tied to your base salary, it's generally not negotiable.
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But the cool thing about that is if you do negotiate a higher base salary, your bonus will increase along with it.
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So keep that in mind as you navigate the negotiation.
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The third comp component you're hopefully gonna receive is gonna be equity as a data scientist.
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It usually comes in the form of either restricted Startup units, RSUs, or employee stock options.
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RSUs are gonna be actual stock, okay, which means you receive shares in the company stock outright once vested.
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You're usually gonna see that at a public company, whereas stock options are gonna give you the right to purchase a company stock at a predetermined price.
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For example, you pay an exercise price to go ahead and exercise those options and then you get the shares, okay?
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And you're gonna find those more like startups or non-public companies.
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Data scientist equity grants are gonna usually come with a stock vesting schedule, which this means you'll need to wait for the equity to invest according to that schedule before you actually own the shares or options.
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Most stock vesting periods are gonna be three to four years with the equity vesting and increments over that time.
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And the stock vesting schedule may be evenly distributed or staggered.
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So, for example, a Microsoft RSU vesting schedule is a four-year period with equal annual vesting amounts each year.
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Okay, so that means 25% you'll get each year.
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Um, so 25% in year one, 25% invest in year two, 25% invest in year three, and the final 25% invest in year four.
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However, you'll find a staggered approach, say at Amazon, where 5% best at the end of your first year, 15% at the end of your second year, 40% of the end of year three, and then the remaining 40% in year four.
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So each company is gonna have their own specific vesting schedule for data scientists, and you need to ask about this when you get the offer.
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One thing about equity is you don't get the full value of the equity up front, but luckily you do share in the value fluctuations over that period.
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So if the stock price goes up, so does the value of your equity as a data scientist.
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The flip side is if the stock price drops, so does your total compensation and your equity value.
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So there are risks when it comes to equity.
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And then if you do leave before your equity fully vs, you are going to forfeit the uninvested portion of your equity.
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So keep that in mind.
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The final component you'll typically see as a data scientist is going to be a data scientist sign on bonus.
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This is usually a one-time cash payment, typically paid out with your first paycheck or 30 days after you start.
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And it's usually designed to offset loss incentives or equity from your previous company.
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But we've also found that you can usually get them just as an incentive to join as a new company.
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All right.
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Data scientist sign-on bonuses aren't always included in the initial offer, so they do often require negotiation.
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Um, but know that we've been very successful in securing them for the data scientists that I work with.
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So keep that in mind and just note that it might take some negotiating to secure one.
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Um, and as for that, like other compensation components you might see is typically going to be on the equity side, where companies that do offer equity to data scientists might also provide annual equity refreshers or stock refreshes, which are additional equity grants each year.
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However, these stock refreshers aren't always guaranteed and they usually vary significantly.
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So it's not an item I would typically include in our total compensation calculations, but you should always ask about these and see if they do exist and see if you can get any details from the recruiter so you have a better idea of what your future compensation might look like.
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Now, these four main data scientists salary components, your base salary, bonus, equity, and sign up bonus, are gonna make up the total compensation as a data scientist at most companies.
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To help you visualize this, we have a total compensation calculator on our site.
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It lets you input your base salary, the bonus percentage, the equity grant, and the sign-up bonus.
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Then it's gonna show you your estimated compensation over the vesting period, both in total and on an annual basis.
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So you can find that free total compensation calculator at thesalarynegotier.com.
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And I'll also link it to it in the episode notes below so you can use this free tool.
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But that way you have a way to actually look at your offer package to see at what you're truly making.
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All right, now the fun part, right?
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We've already covered the data scientist compensation structure and how that works.
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So now I want to discuss the data scientist salary negotiation steps.
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These are the strategies that I've used with many data scientists to help them negotiate their job offers, and I'm gonna recommend you follow to navigate your data scientist salary (https://www.thesalarynegotiator.com/meta-data-scientist-salary) negotiation once you have an offer in hand.
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Now, once you have a data scientist job offer, the first step to negotiating is to make sure you fully understand the compensation components and the benefits in your data scientist offer package.
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The biggest takeaway from this is understanding the data scientist total compensation before negotiating because that way you know exactly how to value the data scientist offer and what to negotiate.
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So that includes the base salary, the bonus, the equity, and the sign on bonuses.
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So don't skip that step.
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The second step is what I call doing your due diligence and asking strategic questions.
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This is where you're gonna review the data scientist offer letter and come back with a list of questions for the recruiter.
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This not only helps you clarify any questions you might have about the offer, but it allows you to strategically ask questions that are gonna build you salary negotiation leverage with the recruiting team.
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Okay, you're gonna go ahead and call out items that might not be as competitive compared to your current company or your competitors.
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And if you need some ideas, I have a full list of strategic questions on what to ask, both on our templates page and in our course.
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That way you know how to strategically draft these and what questions to ask.
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But don't skip this step, okay?
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Even if you think you understand the offer, this step is very important for building negotiation leverage by showing you're doing your research and your due diligence before you send a data scientist counteroffer.
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It also lets you secure any freebies on the items that might be used as trade-offs later on in the salary negotiation.
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So make sure you do it to prevent that later on.
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Now, the third step, which should be big for data scientists, is the compensation research, okay?
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Where we're gonna want to find the base salary and the total compensation ranges for the specific role, location, and level at the new company.
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So we can take a data-based approach.
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All right, you're a data scientist, you should always be leaning on data.
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Don't skip this when you negotiate.
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You can use various online resources to find this data, just make sure you're averaging the results across multiple resources because with this data, it is publicly reported and it might be higher compared to what they might offer a new hire because it includes equity appreciation, or whoever uploaded it maybe didn't understand what total compensation is and missed components.
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So make sure you look at multiple resources and you average across those.
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But if you need, you can use our compensation comparison research tool that's gonna actually help you pull in some of that information.
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So feel free to download that.
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Or I walk through actually how to do the compensation research in a lot more detail in our course.
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So both of those can help you out.
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But essentially in this step, we're trying to find the base salary and the total compensation range for a specific role to find out where the initial offer sits, how much more we should push for.
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So once you have the data scientist compensation research done and you've gotten the answers to all your questions, you're now ready to draft a data scientist counteroffer.
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Okay, so this is where the fun part kicks off, and we take a database approach to craft our data scientist counteroffer and send it to the recruiting team.
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We're gonna present the top end of the range you're targeting based on your research and call out any items that weren't competitive based on the due diligence questions.
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My recommendation is to do this by email.
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And the reason for that is because it's gonna give the recruiter everything they need to advocate for you and send your points to the comp team.
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Instead of hoping that if you counter verbally, that they're gonna take notes of it.
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Plus, if you do counterverbally, the recruiters negotiate offers every day.
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They're gonna know where you're coming and they're gonna cut you off and steer you in a different direction.
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So I recommend against that.
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Um, and the final step, because we know that recruiters are prepared in salary negotiations as well as they negotiate offers every day, is be prepared for pushback after you send a data scientist counteroffer.
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Okay, they're trained to push back on you and they are gonna give you pushback.
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So we wanna overcome that to make sure that your concerns in the counteroffer make it back to the decision makers.
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So to do this, you essentially want to say that you understand their concerns, but nicely reiterate yours and ask them to take it back to the team for another look.
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It's honestly gonna possibly take a couple objections to overcome before they agree to take back yet another look.
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But nine times out of 10, if you do get them to take it back, they will come back with a better data scientist offer package.
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And if you need more details on how to cover these or exactly what to say to do this effectively, feel free to grab my objection handling responses on the templates page or jump into my course for me to talk through that more so you know exactly how to encounter this and how to overcome it.
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So you don't come off as aggressive and you keep the tone friendly and have a strategic approach to navigate that process.
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Um, but as long as you do that and you get them to take it back from here, it's really just a waiting game.
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They're either gonna come back with a better offer that fits your needs, or it's gonna be lower than what you asked or not move at all.
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And at that point, you can either see if you're ready to accept or if you want to take send another data scientist counteroffer.
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The only thing I want to highlight is note that negotiations aren't like what you'd see at like a car dealership or maybe what you thought you saw online in the past, is there's not a lot of back and forth of arguing over numbers.
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Usually you don't want to send more than two counteroffers, otherwise, you do risk coming off as aggressive and jeopardized relationship.
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So make sure you take a strategic approach from the beginning to hopefully get most of the movement in the first counter and then decide if it's worth pressing again or not.
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Okay, so we chatted through the data scientist salary negotiation steps, but there are a lot of mistakes that pop up that I see people do that I want to call out before you negotiate a data scientist's offer letter.
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The main item I recommend against is don't share your salary expectations or your current pay with the recruiting team.
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This is usually only gonna work against you, right?
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I get it.
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You're a data scientist, you're hopefully gonna have some of these numbers in mind and you want to share these, right?
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But that's just gonna work against you.
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And the risk there is if you throw out a number that's lower than what they could offer, there's more likelihood that they'll give you a less compensation package than they could have offered at the low end of their pay range.
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Or since most data scientists roles are within tech companies, if they find out the compensation you're requesting or you're currently making is in line with a lower level than what you interviewed for, they're more than likely gonna downlevel you and bring you in at that lower level.
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So just don't do it.
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And on the flip side, if you think, hey, I'm gonna be aggressive and I'm gonna throw out numbers that are higher just to get a competitive package, be careful because they might be like, hey, we can't afford this data scientist.
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Let's go in a different candidate and stop the recruiting in the interviews now so we don't waste our time.
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So it's not a good strategy and it can risk the opportunity.
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And if you think about it, the recruiter knows exactly how much they can pay for the data scientist role.
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So you want to turn that question back on them to learn more about both the base salary and the total compensation ranges for the positions.
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Then during the negotiation, you can do your own individual research on both um the base salary and the total compensation to see if the ranges they're sharing are truthful or how much you should push for once you have an offer in hand.
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Okay.
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The next mistake I want you to avoid is make sure you're being realistic about what you should ask for in the data scientist counteroffer.
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Way too often do I see scientists ask for way too much that doesn't make sense, right?
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You're either gonna get laughed off at or it's gonna come off as aggressive.
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In some cases, if you come off as too aggressive, you can get the offer ascended.
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So avoid that and always take a data-based approach as a data scientist to make sure you're asking for realistic compensation they can provide.
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Okay, because every company is gonna have set compensation bans and they're only gonna pay within those bands for the specific role level.
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So don't jeopardize the offer by coming off as too aggressive and asking for unrealistic numbers.
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Just don't do it.
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And finally, look, I understand that negotiation might not be the skill set you have that you typically lean on as a data scientist, but it's okay.
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All right, you might feel nervous, but as long as you follow proven strategies and keep the negotiation professional, there's no risk you at risk the offer.
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Okay, so if you do it right, you should secure a better data scientist offer package before starting.
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So have confidence in this, but just make sure you're providing and following proven strategies at work.
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And if you need it, get the support you need to negotiate a data scientist offer package.
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All right, team, that wraps up this episode on data scientist salary negotiation.
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I hope my breakdown of data scientists' compensation structure, our proven data scientist salary negotiation tips and strategies, and the negotiation mistakes to avoid as a data scientist help you feel more confident in these discussions.
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But honestly, if you're serious about getting the best possible offer, I highly suggest you don't go into the salary negotiation alone.
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So feel free to head over to thesalarynegotiator.com to either work with me directly as your salary negotiation coach or check out my salary negotiation courses, templates, and tools.
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You can find all the links in the episode notes below, but those are all designed to help you navigate these conversations and get competitive pay.
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So please use them.
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And honestly, if you found this episode helpful, make sure you subscribe, leave me a comment, and share it with someone who can use this advice in their career.
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So thanks for tuning in and good luck negotiating.