Data Scientist Salary Negotiation: A Comprehensive Guide to Negotiating

Called the “sexiest job of the 21st century” by the Harvard Business Review, data science is an extremely fast-growing field. Given this demand, data scientists often see high compensation and have significant leverage to negotiate. But, as a data scientist, how should you navigate the negotiation process? And what sort of compensation should you expect?

Below we’ll share an overview of the data scientist negotiation process – plus real examples from DS negotiations at companies like Amazon, Meta, Google, and Tiktok, as well as startups. You’ll be armed with all the information you need in order to make your next job offer the highest possible.

Table of Contents

‍Introduction‍

With the rise of tech and internet companies over the past few decades, there has been a similar rise in the field of data science. As Celential.ai describes the role, a data scientist is “part Mathematician, part Statistician, and part Software Engineer.” 

According to the Bureau of Labor Statistics, the data science field is expected to grow 36% in the next ten years! While it’s clearly a growing field, it requires very specific skills and is thus not overly saturated by workers. Machine Learning and Artificial Intelligence (ML/AI) are increasingly innovative fields that fall under the umbrella of data science. As a data scientist, you can find compelling opportunities with strong compensation at ML- and AI-focused companies like AWS, Databricks, Alteryx, DocuSign, and even companies like IBM (which is transforming into more of an AI focus) - as well as nearly every tech company. Often a high-priority role for companies, the cost to hire a data scientist can average around $30,000 (including factors like recruiting tools, job posting websites, recruiter salaries, systems, and per-hour cost for interviewer time). This is similar to the cost to hire a software engineer, although the time to hire a data scientist can often be longer. Since it’s so expensive already for the company to go through the hiring process (before extending an offer), it’s highly unlikely an offer would be pulled due to negotiation - more on that later!

While data scientists don’t seem to be lacking opportunities, the economy certainly plays a factor and it can still be tough to nail down a job and get the best compensation possible. We’ve seen companies like Amazon (who were, at one point, very willing to go above the top of the salary band for quality candidates) now being very hesitant to offer anything even close to the top of the band - and that extends to data scientists. This article aims to help provide the necessary context, both on the market and negotiation tactics, to help secure the compensation and role of your choice.

In this article, we’ll share not only the nuts and bolts of the data scientist world, but also dive into the specificity of negotiating a DS offer. From the leveling structure at most major tech companies (and how to push on that) to step-by-step guidelines of what to do (and what to avoid) in recruiter conversations, this article aims to answer any and all questions about how to negotiate as a data scientist in 2023. 

Understanding Data Scientist Levels

Data scientist salary negotiation begins with understanding how companies level experience and skills. Every organization has its own leveling convention; Amazon, for example, hires data scientists at levels from L4 (Data Scientist I) to L8 (Senior Principal). Microsoft levels range from Level 59 to Level 69 (executive-level) and Meta uses IC3 to IC8. 

Regardless of each company’s specific naming conventions, data scientists (like many professions) typically fall into two standard groupings: individual contributors (ICs) and leadership. Individual contributors are the folks doing the day-to-day work, while managers and other leaders oversee teams to ensure they’re hitting targets and completing the necessary work. Generally, ICs fall into standard level groupings of entry, mid, senior, and principal, while managers can start with a lead or manager title, then evolve into senior manager, director, or higher.

Within the IC career ladder, entry-level data scientists are newer to the field, often recently out of school (undergrad or an advanced degree program). They require more oversight as they learn the ins and outs of the job. Mid-level and senior data scientists have more experience, possibly more education, and are increasingly self-directed. Principal data scientists level up the organization with their unique expertise. As with many other roles, there are varying levels of management from more junior managers or leads to director-level or higher up the executive chain.

Each level has its own compensation band in addition to specific skill requirements and success measurements, so you’ll want to understand how a company determines and assesses data scientist levels. 

Understanding Data Scientist Offers

Although there isn’t one exact formula, data scientist offers at most tech companies (public and privately held) usually consist of similar components, so it’s important to be familiar with them. 

Base Salary

The standard aspect of virtually every job, including data scientist, is the base salary. This is the compensation you receive on your paycheck each pay period. Per our negotiations with data scientists in 2022, we saw base salaries ranging from $179k all the way up to $255k, and that’s just for mid-level folks. If you’re senior (L7 and above), you could potentially get into the $300k base salary range and beyond. While a base salary is included in every offer, it’s typically less negotiable than other components, as it’s the most consistently paid out and the least variable. 

Performance Bonuses

Bonuses take different forms at different organizations. Some offer an annual bonus that is based solely on the company’s achievement against revenue or other goals. Others (more commonly) offer a bonus that is paid out based upon a combination of company performance and individual employee performance. In either case, performance bonuses are typically equal to 5-30% of the employee’s base salary and are not a guaranteed part of one’s compensation. For example, at TikTok, they quote everyone a 25% annual bonus (regardless of leveling placement or job title), but it’s widely known throughout the company that actually achieving 25% is very unlikely. Some companies provide bonuses only for certain levels or offer different amounts per level. 

Equity - RSUs vs. Stock Options

Many tech industry jobs, including data scientist positions, include equity as a large component of their offers. Equity, often provided in the form of restricted stock units (RSUs) or stock options (typically referred to as ISOs or NSOs), is simply stock in the company. 

If a company is publicly traded - like Amazon, Microsoft, Facebook (Meta), Google, and others - they usually offer RSUs. This means the company awards shares to you at no cost (other than taxes). RSUs shift in value depending on the stock market and economic conditions, but because they are actual publicly-traded shares, they retain some level of cash value. Although it’s rare, it is possible for a privately-held company to offer RSUs, which don’t come at a cost to you but are also not liquid and thus not easily sold - TikTok, Snowflake, and Airtable all do this! 

On the other hand, startups or pre-IPO companies frequently award stock options. Because the company is not yet public and doesn’t have the ability to offer official shares, they give you the right to purchase (or “exercise”) a number of shares at a given price (known as the “strike price” and often much lower than the eventual price at IPO). There is a lot of upside to joining an early-stage company but there is also a lot of risk. In the unfortunate case where the company never goes public, you may be left holding equity that is worth little or nothing. That said, if the company does go public, you could see a strong upside. Just think of the folks who worked at Amazon in their startup days!

Regardless of the type of equity you receive, it comes with a “vesting schedule.” This is the timeframe within which the company will pay out your shares. In the same way you don’t receive 100% of your annual salary on your first day, you don’t receive all of your equity right away. The vesting schedule also helps keep the amount of your equity more stable as the stock market rises and falls. 

The most frequently-seen vesting schedule is as follows: you receive 25% of your equity each year over four years, after a one-year cliff (in other words, you are obligated to remain at the company for a year before receiving your first portion of vested stock). Although common, the 25% vesting schedule isn’t universal, and many large companies (think Amazon, TikTok, and Google) have different equity philosophies. For example, Amazon backloads their equity vesting so that instead of an equal amount each year, you receive 5% of the equity in your first year, 15% in the second, and 40% each in years three and four. In order to collect all the equity awarded to you, you need to remain at the company for the entirety of the vesting period. Since equity is subject to a company’s board or the stock market, these vesting schedules are not typically negotiable, especially at large companies. 

If you’d like to learn more about the different types of equity and gather startup-specific equity negotiation tips, check out our blog post here.

Signing Bonus

Companies may offer a signing bonus to seal the deal with a highly sought-out candidate, especially an in-demand data scientist. Although signing bonuses aren't a guaranteed part of an offer (and they’re frequently not included in the initial offer until you’ve negotiated a bit), you can always ask for one. They’re typically one of the easier levers for a company to pull. While some companies offer a one-time bonus paid out on your first check, others (notably Amazon) offer a bonus split out across your first two years of employment (Amazon does this to help offset the backloaded equity vesting schedule and keep your compensation more consistent each year). The standard signing bonus range we’ve seen for data scientists is between $25k-$50k for a public company, $10k-$30k for a private company (depending on size). 

Be aware that your offer letter may include a clawback policy; this means that if you leave the company before a certain timeframe, you’ll be required to pay back the sign-on bonus either in full or a prorated amount. This will usually be listed in the offer letter, so make sure you understand the conditions. Recently, TikTok updated their clawback for signing bonuses to require two years at the company - so if you leave before then, it’s likely they’ll ask for a prorated amount of your bonus back. 

Other Common Offer Components

Compensation is certainly a large and important piece of a data scientist job offer, but there are other aspects to think about. Pay attention to paid time off (PTO), health insurance coverage, 401(k) or other retirement plan match, visa or green card sponsorship, and overall flexibility (even a company that has required a full return-to-office may still be willing to negotiate remote or hybrid work for a top candidate). 

Most companies offer some combination of the above but the specifics differ depending on company size and other factors. Large or mid-sized companies often have more cash to offer compared to a startup, but it’s still common for equity to be a large part of any data scientist’s offer. Earlier in your career you may see base salary as a larger component than equity, but as you become more senior the reverse is often true. 

Larger companies may have more cash, but they also have more standardized procedures, which can lead to less wiggle room. It may be easier at a small company or startup to negotiate for something like increased PTO. If excellent health insurance or a substantial retirement plan match are important to you, you’ll be more likely to find them at a larger company. 

For your reference, we’ve compiled compensation bands for some top companies here:

• Microsoft Data Scientist
• Amazon Data Scientist
• Google Data Scientist
• TikTok Data Scientist

Data Scientist Offer Process

In order to prepare for negotiations, it’s helpful to understand the process from interview to offer. Interview processes vary by company, but in all cases they use that time to determine your fit within the company and role. You should view the interviews as a time to do the same and ensure all of your questions are answered. After the interview, the hiring manager and interview panel debrief on next steps; often, this is when they assess your performance in the interview to determine the level. Your prior skills and experience come into play here, too, but it’s not unheard of for someone to be offered a different level than they initially interviewed for. It’s possible to push back in these cases and even reinterview if necessary; we’ve seen success in making those asks with the hiring manager directly. One hiring manager at Microsoft even told us to always advise our clients with Microsoft offers to ask for an uplevel because misleveling is so common in the interview process! The worst they can say is no.

Once these decisions have been made, the recruiter and hiring manager seek approval for an official offer (often from a hiring committee made up of company leaders, a la Google) and present it to you upon approval. 

You Got An Offer - Now What?

Before you can negotiate, the first step is to know your requirements. Ideally, you’ll be clear on this before starting your job hunt so you can fully assess each opportunity. 

There are a few aspects to consider: your walk-away number, your target, and your aspiration point. Your walk-away point is the absolute lowest you could accept; anything less and you’ll walk away. Your target is the number you’d be really happy with (maybe it’s 20% higher than where you’re earning today, maybe it’s enough to allow you to start saving for a house – ultimately this number looks a bit different for everyone), while your aspiration point is the number that would make you accept the offer on the spot. We recommend starting high and working your way down - would you sign on the spot for one million? $900k? $800k? etc.

How do you come up with these numbers and determine what’s reasonable? To start, you’ll want to factor in market data. One thing to note is that cost of living surprisingly doesn’t factor in as much to compensation from the company's perspective, as they go off of the market rate for engineers in that area. That’s why you see folks in the Bay Area (higher density of engineers) get strong comp, but folks in Chicago (still an expensive city, but with fewer engineers) get paid less. That’s not to say that cost of living isn’t personally important, but note that companies don’t typically make movement on offers based on that reasoning.

To find data scientist salaries, focus on sites like Levels.fyi, Blind, and even H1-B visa filing data (for base salaries). Skip sites like Glassdoor for compensation research, as their accuracy for technical roles is low (Glassdoor can be helpful to get context on the employee experience at that company, so we do recommend perusing the reviews section of the company page). 

You can also view job postings in the few states whose laws require companies to include pay ranges in job postings (including Colorado as of 2022 and Washington state as of 2023) - but note that these ranges may be portrayed as lower than they really are. If the actual range for a role is $100k-$200k yearly comp, expect to see the posted range as $90k-$130k. Don’t hesitate to ask your network or mentors, as well. It may be tempting as a data scientist to rely solely on market data, but that’s only one part of the negotiation. Think through the value you place on the skills and experience you bring to the table. You also need clarity on what compensation is in line with your lifestyle, expenses, and desires. 

Once you’ve decided on your walk-away number, your target, and your aspiration point, you’ll need to figure out your actual ask. Negotiation isn’t usually as simple as asking for a number and receiving it. See below for more context on how to structure your ask!  If you’re offered $100k and you ask for $150k as your target, the company will likely come back with a number somewhere in the middle. Avoid that hassle by shooting closer to your aspirational number - this is called “anchoring.” In the worst case scenario, you get something closer to your true number, and in the best case, you get what you asked for! 

Salary is, however, only one part of the offer. Determine what is most important to you. For some, equity is enticing as it enables them to benefit from a company’s long-term growth, but for others the stability of a higher base salary is more comforting. Some folks may feel that as long as their bills are paid, money isn’t the most important - they’d rather target workplace flexibility or generous vacation time. You don’t necessarily have to sacrifice one component for another, but it’s helpful to have an idea of what matters most to you. 

How Is An Offer Determined?

Understanding the data points that go into a data scientist offer is key to successfully negotiating. 

As you know, your previous experience and your performance in the interview are factors in what you’ll be offered. As each level has an associated pay band, the level at which you’re placed will determine your salary range and your experience and interview performance can impact where you fall within that range.

Your education can also impact the offer you receive. If a role requires a Master’s degree and you have a PhD, you can ask for more money based on the education and expertise you bring. We’ve seen some PhD’s nab first offers of $850k yearly comp based on their level of understanding and their specific PhD field of study (Data Science, Statistics, and Machine Learning tend to yield premiums), so it’s definitely possible to get a strong offer by leveraging your education. Rare skill sets or highly desired experience can also lead to higher offers. Those who work in machine learning, for example, often receive higher offers due to the challenge of finding qualified talent. 

Although pay bands are based on level, they sometimes take location into consideration. Companies choose whether they anchor pay to a single location (for example, a company in Seattle paying Seattle salaries even to folks working in Chicago) or whether they offer location-dependent pay (e.g. a Meta data scientist in Chicago earning pay based on the local market rate instead of the Bay Area’s market rate). Location-dependent pay means that even in an expensive city like Chicago, you will earn less than an employee in the Bay Area due to the difference in market rate. That said, even in this situation, you can and should ask for more.  

Finally, your offer can be affected by competing offers (or even final interviews) from other companies. If you have other offers that are higher than this company’s offer or if you’ve discussed competitive compensation with another company but don’t have a formal offer yet, you may be able to use it to your advantage.

What are the Most Negotiable Aspects of a Data Scientist Offer?

Between base, equity, and signing bonus, the most negotiable component is usually the equity grant. Companies don’t want to pay out more guaranteed cash so they prefer to give equity as it’s more variable. 

That said, it’s worth asking about almost everything included in your offer package, including all aspects of the compensation (except for the annual bonus percentage, which is typically not negotiable unless your level is changed). If you’ve hit a dead end when it comes to higher compensation or more paid time off, consider asking for more flexibility (like remote work or flexible hours). If you’re a work visa holder and hoping to apply for a green card immediately, that’s often negotiable as well. 

Refer back to what you know about data science levels at this company. If you’re aligned with the level they’re offering in terms of scope of role and compensation, great. If not, ask the recruiter to explain the difference in day to day work and overall impact from this level to the next one up, then use that to compare your experience against both. Ask to speak to the hiring manager and use that time to understand why they placed you at the level they did and whether there is any flexibility in that decision. If after these conversations you feel you should be considered for a higher level, speak up! Sometimes companies will allow you to undergo an extra interview to prove your skills. A higher level brings with it higher compensation, so it’s absolutely worth the ask. It is important to note that even if your uplevel request ends up getting denied, just asking can give additional justification as to why you need strong compensation. We had a client who was negotiating with Amazon and hoping to get from L6 to L7. Amazon agreed to reinterview the candidate but decided to hold on moving them up to L7 - but they did agree to go above the top of the compensation band to make up for it. 

How to Negotiate

Negotiation is a process you should be thinking about from the very beginning, not just when the offer comes in. This means you should engage in strategic conversations with the recruiter and hiring manager, be clear on your leverage points, and communicate effectively. 

It’s likely that early in the interview process the recruiter will ask about your job search or compensation requirements. You may wonder how honest to be or what information you should share. It’s important to understand the purpose of these questions: recruiters typically ask so they can be sure the role aligns with what you’re looking for (whether that’s compensation, your motivations, or general preferences). That said, there is no obligation to provide details and we recommend you keep it close to the vest and instead seek for the recruiter to provide the first number.

If you’re asked about your current salary, you never have to share this information. In many U.S. states, it’s actually illegal for prospective employers to ask, and you can simply say you prefer not to share. If the recruiter asks for your target compensation, you still don’t have to provide details (although it is legal for them to ask). Expect to be asked in almost every interview process and be ready with a response. 

One option is to share your number, but we generally advise against this in most cases. One exception: if you’re making a switch from a high-paying industry to one that pays less (for example, leaving the for-profit world for a non-profit), it might make sense to share a number to provide an anchor.  

A better response is to seek further information. Replying with something like, “I’m not sure I know enough about the role or company to make a strong determination just yet, but is there a range budgeted for this position?” will usually get you the detail you’re looking for. It’s worth noting that in some states, recruiters are legally obligated to share the pay range with you if you ask (the California Equal Pay Act is an example). Once you know the range, you can respond accordingly - whether that’s agreeing to move forward or stating that you actually require a higher number.

Once you’ve received an offer, take some time to review the details. Your recruiter will almost always ask when to expect a response from you, but there is usually less urgency than it appears. We always recommend folks take at least a few hours away from the offer before diving into analysis - emotions run high when you receive a job offer! Saying something to the effect of, “Thank you for all of these details. I’d like to take some time to review everything/discuss with my family and come back with my thoughts,” is completely fine. 

When you are ready to think through the details, refer to the numbers you determined earlier and ask yourself: does this offer align with your ideal compensation? Are important components present or missing? This will give you a clearer picture of what to ask for next.

After you’ve determined your ask, decide on your rationale. Keeping in mind what you know about how offers are crafted, backup your request for more money. Do you want to reiterate the skills or education you bring to the table? Provide market data in favor of higher compensation? Request a review of your level? If there is evidence that you’re qualified to come in at a higher level, now is the time to make that argument. If you have competing offers, feel free to reference them (if you don’t have any, don’t fib, but instead you may want to reference being in consideration for other opportunities).

You should also consider what you’d need in order to walk away from your current company. Even if your current job doesn’t pay as well, you may receive other benefits the new job lacks, like unlimited PTO, more flexible hours, or something else that makes it difficult to walk away. You might be expecting a bonus that you’d be walking away from if you left today, or you may be subject to a clawback policy. Don’t hesitate to express these needs. And don’t forget that there are always trade-offs: if there is something missing from your offer (for example, a retirement match), try asking for more of something else to make up for it (like a signing bonus). 

Remember that you and the company have the same goal: for you to join as their newest data scientist. It’s expensive (in terms of dollars and opportunity cost) to recruit and hire someone, so they truly benefit from making a deal with you rather than starting all over. And try not to worry - if you negotiate respectfully, it’s unlikely any company would pull the offer.

When you have the offer in hand, we recommend booking a call with your hiring manager to ask any questions you didn’t get to ask during your interviews and continue to build a strong relationship. Consider coming to the meeting with what we call an “impact roadmap” (also known as a “30/60/90 day plan”) - this can show the hiring manager how you plan to approach the new role and give them the confidence that you’re thinking critically about how to be successful. It’s also a chance to make sure your priorities are aligned and earn more buy-in from the hiring manager, who will be more likely to support your request for a higher offer.

Once you’ve finalized the numbers you want to counter the offer with (remember to shoot higher than you actually want) and gathered the data to back it up, set up a call with the recruiter. Keep it short and to the point; something like this will suffice: 

“Thank you again for sending over all of the offer details. I reviewed everything over the last few days, and based on what I’d need to walk away from my current company, , as well as the offer I have from [company B], if [company A] was able to get the compensation to [desired amount], I’d be happy to sign with [company A] today.”

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Then, and this is important, stop talking! You may feel like you need to keep justifying or explaining, but silence is actually your best bet. If the recruiter asks for more context, you can share your thoughts then. 

What if you have specific requests rather than just an increased total compensation number? Maybe you want a higher base and more equity, or you’re happy with the base pay but want a signing bonus and better PTO. Try something like this:

“Thank you again for sending over the offer details! I took some time to review everything, and while I’m excited by the team and the role, what I’m struggling with is how I can walk away from the 10 weeks of PTO offered by my current employer. I will also be missing out on my annual bonus at [current company] if I leave now, so if [company A] was able to add a signing bonus of [dollar amount] and an additional two weeks of vacation, I’d be excited to sign.”

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It may help to think about this as an “excitement sandwich.” This means starting the conversation by reiterating your interest in the company and job, stating your reservations and what’s keeping you from accepting, then finally sharing your excitement and intent to sign if they can meet your terms. This simple formula covers all of your bases: it’s apparent you’d like to join the company, but it’s also clear you need them to sweeten the pot.  

If you’re nervously thinking, “Wait, I have to do all of this over the phone?!” you’re not alone. We get it! But it’s true - negotiating via a live conversation is more effective than doing so via email. An email negotiation carries more risk, drags the process out longer with more back and forth (and room for misinterpretation), and lacks the rapport you can build in a live conversation. However, if it’s between an email negotiation or no negotiation at all, go with email - just be careful about it (we’ve got tips here). 

Don’t worry about losing the offer if you negotiate. If you negotiate in a manner that is reasonable, respectful, and timely, no legitimate company will pull your offer. After all, they see your skill and talent and are expecting you to advocate for your own earning potential. Companies will only rescind their offers if you demonstrate yourself to be a liability to the company (saying offensive things, showing yourself to be a dangerous individual) or if their needs change, which means your role would have been at risk of being cut anyway. The chance you’ll lose an offer from respectful negotiation is below .05%. If you fall into that 05.%, it’s not a company you’d want to work for. 

Mistakes to Avoid

Knowing how to negotiate is imperative, but you should also know what not to do. Here are a few common negotiation mistakes we want to help you avoid. 

Mistake #1: Not negotiating at all: It’s true: one of the best ways to lose out on a higher offer is to not negotiate at all. Even in a perfect situation where your first offer comes in higher than you dreamed, it will never be easier to negotiate than at the offer stage. Even if you only ask for additional flexibility or a small sign-on bonus, make sure you ask for something.

Mistake #2: Negotiating without a clear strategy: You need to start the negotiation with a strong point of view that is backed up by data. Prepare for your conversations by reviewing the reasons for your ask and getting familiar with the various components of the offer. Having a strategy and sticking to it will lead to a stronger deal.

Mistake #3: Negotiating after signing the offer: One reason it’s important to stick to the strategy is that you don’t want to end up with buyer’s remorse. Once you sign the offer, you’ve effectively agreed to the terms as-is and committed to joining the company. If you go back on your word and try to negotiate post-signing, it will appear as though you signed in bad faith - and will be ineffective, since the company isn’t likely to offer more when you’ve already agreed to the terms. The time to negotiate is always before you accept.

Mistake #4: Negotiating based only on what you want: You’re working to earn a living, so of course your needs and desires are important. However, there are two sides involved here and the goal is to reach a mutual agreement. You’re unlikely to succeed if you only focus on what’s in it for you. 

Salary negotiation is no easy task - for data scientists or anyone -  but advocating for yourself is a skill you’ll be glad to have. Keep in mind that not only do you have a unique, high-demand skill set, but the company has assessed multiple candidates and chose you. Negotiating to reach terms both sides are happy with sets the employment relationship up for success and will get you started on the right foot. 

You’ve got this! If you’re looking for more hands-on support, we’re available; sign up for a call with a Rora negotiation coach!