TL;DR
Data Scientist Salary in the US is one of the most searched numbers in tech, and one of the most misunderstood. Google it and you will land on five different figures from five different sites, and none of them are lying. They are just measuring different things.
That gap is exactly what costs candidates real money. You compare a $145,000 offer against a Glassdoor average and think you nailed it, only to learn later that a peer at the same level pulled in $250,000 once RSUs and bonus hit the table.
This guide breaks the number apart properly: real 2026 pay by level, company, and remote status, straight from BLS, Glassdoor, and Levels.fyi. For a broader look at what other tech and data roles pay right now, our salary guides hub is worth a look too.
What Data Scientists Actually Earn Right Now
If you have spent the last hour bouncing between Glassdoor tabs and Levels.fyi screenshots trying to figure out what a data scientist actually makes in 2026, you are not alone. Every site seems to report a different number, and none of them are technically wrong.
The Bureau of Labor Statistics (BLS) puts the national median annual wage for data scientists at $112,590 in its most recent full release, with a newer 2025 update pushing that figure to $120,230. That number covers every employer in the country, from insurance companies to government agencies to hospitals, and it only counts base pay.
Glassdoor salaries for the same role average closer to $126,000 base, weighted toward larger metros and tech-heavy employers. Indeed salary data lands a bit lower, around $118,000. None of these three sources are chasing each other. They are each measuring a slightly different slice of the same job title.
A lot of people researching this role actually start out one step earlier in the pipeline. If that describes you, our full breakdown of the data analyst salary in the US for 2026 walks through the pay you can expect before you make the jump into a data scientist title, along with the skills that speed up that transition.
Why Every Salary Site Gives You a Different Number
Here is the part most guides skip. Levels.fyi compensation data comes almost entirely from people working at companies that hand out equity, so its median total compensation figure of around $176,000, with a 75th percentile near $245,000, reflects a richer and narrower slice of the market than BLS ever will.
BLS measures base pay across the entire economy. Levels.fyi measures total pay at stock-granting tech employers. Both numbers are accurate. They are just answering different questions, and mixing them up is the single biggest reason job seekers misjudge their own offers.
Salary by Experience Level
Entry Level (0 to 2 Years)
Entry-level data scientists with a bachelor’s degree average roughly $95,000 to $101,000 in base pay, according to aggregated Zippia and BLS figures. Add a master’s degree and that starting number climbs closer to $109,000 to $130,000, particularly at companies that hire directly from data science graduate programs.
Mid-Level (3 to 6 Years)
Mid-level data scientists in the US land between roughly $138,000 and $175,000 in base salary as of 2026, per current market surveys. This is usually where SQL and basic analytics work gives way to real modeling responsibility, and where fluency in Python, TensorFlow, or PyTorch starts to matter for pay.
Senior (7 or More Years)
Senior data scientists typically earn $157,000 to $210,000 in base pay, with total compensation at well-funded tech companies running $310,000 to $420,000 once equity and bonus are included.
Principal, Staff, and Lead Roles
At the staff and principal level, especially at AI labs and FAANG companies, total compensation clears $500,000 and can reach $750,000 or more, with equity making up the largest single component of pay.
What Amazon, Meta, Google, and Microsoft Actually Pay
Company-specific numbers tell a clearer story than national averages. Here is what current 2026 Levels.fyi data shows for four major employers, next to the national base-only average.
| Company | Entry / Low End | Median Total Comp | Senior / High End |
| Amazon | $195,000 (L4) | $259,000 to $260,000 | $763,000+ (L8) |
| $180,000 (L3) | $319,000 | $765,000+ (L8) | |
| Meta | $156,000 (IC3) | $320,000 to $342,000 | $1.11M+ (IC8) |
| Microsoft | $158,000 | $251,500 | $559,000+ |
| National Average (all employers, base only) | $95,000 to $101,000 | $118,000 to $122,000 | $165,000 to $210,000 |
Amazon caps base lower than peers and makes up the gap with sign-on bonuses and back-loaded stock. Meta generally offers the highest base and largest initial grants, at the cost of a demanding pace. Google’s stock units, called GSUs internally, vest on a schedule tied to grant size rather than a flat four-year curve.
Base Salary vs Total Compensation: The Part Most Offers Hide
Here is a scenario I see constantly. A candidate gets two offers: $145,000 flat, or $130,000 plus $40,000 in RSUs over four years and a $15,000 signing bonus. On paper the first offer looks bigger. In year one, the second one almost certainly pays more.
Base salary is the guaranteed part of your pay. RSUs vest over a set schedule, usually four years, and their value moves with the stock price. A signing bonus is a one-time payment, sometimes clawed back if you leave early. Annual bonuses stack on top of that. Reading an offer by base alone is the most common way job seekers underestimate what a role is actually worth.
Remote Data Scientist Salary in 2026
Remote data scientist salary figures vary more than almost any other slice of this market. ZipRecruiter puts the current national average at roughly $122,738 a year, with the middle 50 percent falling between $98,500 and $136,000. Built In reports a higher average of $159,290, likely because its sample skews toward larger tech employers.
Industry matters more than most people expect. Healthcare-focused remote data science roles have reported averages closer to $165,000, well above the general remote average, largely because clinical and claims data work commands a specialization premium.
Does a Master’s or a PhD Actually Pay Off?
About 55 percent of working data scientists hold a master’s degree in data science, statistics, computer science, or a related field, while roughly 13 to 22 percent hold a PhD in statistics, computer science, or machine learning, depending on the survey. The rest came in with a bachelor’s and built the rest through experience.
A PhD holder’s average reported salary sits around $248,000, well above the master’s-holder average, but that gap narrows considerably once you control for the type of role. In the top 75 percent of earners, the difference between a master’s and a PhD shrinks to around $10,000.
Where a doctorate pays off most clearly is in research-heavy roles at AI labs working on generative AI systems, not in generalist analytics work.
H-1B Sponsorship and Data Scientist Pay
Data scientist roles remain one of the more commonly sponsored H-1B categories, with over half of tech-adjacent petitions filed by mid-size employers rather than only the largest companies. Prevailing wage rules from the Department of Labor set a wage floor tied to role, location, and experience, so sponsorship does not typically mean lower pay for the same job.
A wage-weighted lottery system for H-1B selection took effect in 2026, meaning higher offered salaries now directly improve selection odds. That has quietly pushed some employers to sweeten offers for foreign-national candidates rather than lowball them, the opposite of what a lot of job seekers assume.
What Actually Moves Your Salary
Common Salary Myths, Corrected
Myth: A data scientist title always means six figures in stock.
Only at stock-granting tech employers. Government, nonprofit, and many healthcare or education employers pay mostly in base salary with little to no equity.
Myth: BLS numbers are outdated or wrong.
BLS measures base pay across the full national labor market, not just tech hubs. It is the most neutral figure available, not the most generous one.
Myth: A PhD guarantees a bigger paycheck than a master’s.
Only in research-heavy and AI lab roles. In general industry analytics work, the gap between a strong master’s-holder and a PhD-holder narrows sharply.
Myth: Remote roles always pay less than on-site roles.
Pay varies more by industry and company size than by remote status alone. Some remote healthcare and finance roles now out-earn general on-site tech roles.
The Ten-Year Salary Growth Timeline
Years zero to two typically mean $95,000 to $130,000 in base pay while you build core modeling skills. Years three through six move you into the $138,000 to $175,000 range as you take ownership of full projects rather than tasks.
Year seven and beyond is where the curve bends, with senior and staff-level total compensation reaching $310,000 to $500,000 or more. What accelerates it: changing companies at the right moments, negotiating your level carefully at hire, and specializing in generative AI or applied machine learning. What slows it: staying too long in one seat with weak internal leveling, or accepting an under-leveled offer early and never correcting it.
Data Science vs Other High-Paying Tech Career Paths
Data science is not the only technical field with this kind of pay ceiling. If you are weighing your options more broadly, it is worth looking at how a security-focused path compares.
On the leadership end, our CISO salary guide breaks down what security executives earn once you reach that level, which mirrors the staff and principal jump you see in data science.
If you are earlier in your career and comparing entry points, our guide on becoming a cybersecurity analyst without a degree covers a path that, unlike data science, does not usually require a master’s to get started.
For a fuller side-by-side, our cybersecurity career path guide and our breakdown of cybersecurity salary by company lay out how pay progresses by employer, similar to the company table above.
And if remote flexibility matters as much as the paycheck, our guide to remote cybersecurity jobs in the US is a useful comparison point against the remote data scientist figures covered here.
Frequently Asked Questions
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What is the average data scientist salary in the US in 2026?
Base pay averages roughly $112,590 to $122,000 depending on the source, while total compensation at major tech employers commonly runs $250,000 to $340,000 once equity and bonus are included.
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Do data scientists need a master’s degree?
It is not strictly required, but roughly 55 percent of working data scientists hold one, and it typically raises starting pay and speeds up qualification for senior roles.
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Is a PhD worth it for a data science career?
It pays off most clearly for research-focused and generative AI roles at AI labs. In general industry analytics work, a strong master’s-holder often earns close to what a PhD-holder earns.
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How much do remote data scientists make?
Estimates range from about $120,000 to $159,000 a year depending on the source, with healthcare and finance roles often paying above that range.
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Do companies sponsor H-1B visas for data scientists?
Yes. It is one of the more commonly sponsored roles in tech, and prevailing wage rules mean sponsored candidates are generally paid at market rate for their role and location.
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Why do Glassdoor and Levels.fyi report such different numbers?
Glassdoor and BLS numbers lean toward base pay across a broad set of employers. Levels.fyi is built on self-reported total compensation from people at stock-granting tech companies, which pulls its median well above the broader market.
A Quick Note on Where This Data Came From
Every figure here comes from publicly available 2026 data from the Bureau of Labor Statistics, Glassdoor, Levels.fyi, Indeed, ZipRecruiter, and Built In, current as of September 2026. Nothing is estimated or invented. This guide exists to help job seekers understand their own market value, not to recruit for any employer.
Shahzada Muhammad Ali Qureshi (Leeo)
I’m Shahzada — a software engineer by education and an SEO professional by trade. I built WhatIsTheSalary.com to go beyond just showing salary numbers — every page is manually researched across sources like BLS, Glassdoor, LinkedIn Salary, and PayScale to give you the full picture in one place. If you found what you were looking for here, that’s exactly the point.
