Data Scientist Salary 2026: Real Numbers by Level, Company, and State

The Quick Answer

Data Scientist Salary by Experience Level

Compensation broken out by seniority tells a more useful story than any single average, largely because the range widens dramatically as you move up.

Entry-level (0 to 2 years)

PayScale reports an average total compensation of $88,797 for data scientists with less than one year of experience, based on nearly a thousand submitted salaries. Glassdoor's self-reported entry-level range runs from $84,408 to $178,588, a spread wide enough to suggest "entry-level" means very different things depending on the employer. Recruiting firm KORE1 puts a realistic entry-level floor closer to $95,000. A 2026 compensation analysis from Cadence estimates entry-level base pay between $85,000 and $110,000, with total compensation at top-tier tech employers reaching $140,000 to $185,000 once bonus and stock are included.

Mid-level (3 to 6 years)

PayScale's figure for data scientists with one to four years of experience rises to $101,971 in average total compensation. Cadence's 2026 estimate for mid-level puts base pay between $115,000 and $150,000, with total compensation at top-tier employers climbing to $200,000 to $290,000. Motion Recruitment's 2026 IT Salary Guide lines up closely, citing a national mid-level range of $138,000 to $175,000.

Senior (7 to 10-plus years)

Cadence estimates senior base salary between $165,000 and $210,000. KORE1 puts the realistic ceiling for individual contributors before hitting principal-level titles closer to $260,000 in base pay, with total compensation at top tech employers crossing $330,000.

Principal and staff

This is where company-specific data from Levels.fyi becomes more useful than any national average, since the highest bands vary enormously by employer. Reported total compensation includes figures above $760,000 at both Google and Amazon at their most senior individual contributor levels, though these represent the extreme high end rather than a typical outcome.

Data Scientist Salary by Company

Company-level data tells a very different story than national averages, and this is where the biggest gaps between sources show up.

Source: Levels.fyi, self-reported compensation data current as of August 2026.

Levels.fyi also reports that the single highest-paying employer for data scientists in its dataset is Citadel, a quantitative trading firm, with average total compensation of $533,750. That is not a typo relative to the Big Tech figures above. Quantitative trading firms tend to out-pay even the largest tech companies for this specific role because a marginal improvement in a model's predictive accuracy translates directly into trading profit, in a way that is harder to measure and monetize in a typical product organization.

Data Scientist Salary by State and City

Location still matters, though less than it used to now that remote work is common, and cost of living changes the picture more than the headline number suggests.

Washington state reports the highest nominal state median at $158,760, driven heavily by the concentration of large tech employers around Seattle. Adjusted for cost of living, that figure comes down to $146,239, still strong but a meaningfully different number. Washington, D.C. reports a median of $137,120, reflecting demand from federal agencies and their contractors. California and Massachusetts, both states with a significant biopharmaceutical industry presence, report medians of $136,800 and $132,250 respectively.

For remote roles specifically, Motion Recruitment's 2026 guide reports a national range of $141,000 to $180,000 at the mid-level, landing close to major-metro pay without requiring a relocation.

Data Scientist Salary by Industry

Industry affects pay more than most job seekers expect, sometimes more than company size does. Glassdoor's industry breakdown lists Personal Consumer Services as the highest-paying sector for data scientists, at a median of $160,026, followed by Arts, Entertainment, and Recreation at $158,419, Agriculture at $152,767, Information Technology at $148,226, and Financial Services at $147,580.

That ordering surprises people who assume tech companies automatically pay the most. In practice, a handful of well-funded employers in a smaller industry, a streaming platform doing heavy personalization work or an agricultural technology firm building yield-prediction models, can pull that industry's median above much larger, more heavily surveyed industries like general IT. Data science sits closer to the core product in these cases rather than functioning as a support role, and pay tends to follow how central the work is to revenue. The practical takeaway: when comparing two offers, weigh how central data science is to the company's actual business model, not just the industry label on the job posting.

Base Salary vs. Total Compensation

This distinction explains more of the confusion around data scientist pay than any other single factor. Base salary is the fixed amount paid regardless of company performance. Total compensation adds an annual cash bonus, and at public or well-funded private companies, the value of stock grants that typically vest over three to four years.

The details of vesting matter more than most candidates realize. Amazon, for example, has historically used a back-loaded vesting schedule where a new hire receives roughly 5 percent of their stock grant in year one, 15 percent in year two, and 40 percent in each of years three and four, meaning the early years of an Amazon offer look considerably less generous on paper than the total grant value suggests. Google refers to its stock units as GSUs rather than the more common RSU, though they function the same way.

Sites that lean on self-reported base salary, like PayScale and much of Glassdoor's dataset, tend to undercount total earning potential at companies with significant equity components. Sites like Levels.fyi that specifically track total compensation will always report higher numbers than a pure base-salary source, not because either is inaccurate, but because they are answering a different question. For anyone evaluating a contract or fractional engagement instead, ZipRecruiter's 2026 average annual figure translates to roughly $59 an hour, a useful starting benchmark before negotiating a contract rate.

How AI Is Reshaping Data Scientist Pay in 2026

This is the part of the conversation that barely existed two years ago and is now impossible to ignore. A 2026 compensation analysis from Cadence observes that large language model coding assistants have become reliable enough to handle routine junior-level tasks, including basic SQL queries, exploratory data plotting, and first-pass feature engineering, tasks that used to make up a meaningful share of an entry-level data scientist's actual workload. Smaller and mid-sized companies have increasingly shifted that work to senior data scientists working alongside AI coding tools rather than hiring additional junior staff, compressing entry-level hiring volume even as the roles themselves have not disappeared.

This does not mean data science as a field is shrinking. Quite the opposite: 365 Data Science's 2026 job market research found that machine learning skills appear in roughly seven in ten data scientist job postings, and that demand for natural language processing skills specifically nearly quadrupled, rising from about 5 percent of postings to 19 percent year over year. Cloud certification requirements, such as AWS credentials, now show up in close to one in five postings as well.

Data Scientist vs. Data Analyst vs. Machine Learning Engineer Pay

Job titles in this field are inconsistent enough across companies that comparing pay by title alone can be misleading, but government wage data offers a useful, apples-to-apples starting point.

In practice, the gap between a data analyst, a data scientist, and a machine learning engineer has as much to do with scope as with title. Analysts typically focus on reporting and descriptive work. Data scientists add statistical modeling and experimentation on top of that. Machine learning engineers typically own production deployment, which pulls the role closer to software engineering pay scales, one reason the closest BLS category reports a meaningfully higher median. If you want to see where your own knowledge lines up, our Data Science Interview Quiz covers this kind of role-scope question directly.

How to Negotiate a Higher Data Scientist Offer

A few practical steps make a measurable difference once you have an offer in hand.

Frequently Asked Questions

Conclusion: Read the Number, Then Read the Source

Every data scientist salary figure in this guide is accurate for what it measures. The only mistake is treating any single one of them as the complete picture. A government median, a self-reported average, and a big-tech-skewed total compensation figure are three different measurements of three overlapping but distinct populations, and knowing which one you are looking at matters more than the number itself.

The figures above come from three source types cross-referenced against each other: the Bureau of Labor Statistics for a base-wage, methodologically neutral benchmark; aggregators like PayScale, Glassdoor, and ZipRecruiter for self-reported, directional figures; and Levels.fyi for company-specific total compensation at large tech employers. Industry analysis draws on Motion Recruitment, KORE1, Cadence, and 365 Data Science. This guide was last updated in August 2026, and since compensation data changes frequently, treat every figure here as a benchmark to check against current, company-specific offers rather than a guarantee.