Data Scientist Salary Overview
A Data Scientist in the United States earns a median of $108,020 a year, or about $51.93 an hour over a full-time year of 2,080 hours. A Data Scientist spends their workday extracting insights from large datasets, building predictive models, designing A/B tests, communicating findings to stakeholders, developing machine learning pipelines, creating dashboards and visualizations, and collaborating with product teams on data-driven features. The band runs from $62,400 to $184,800, a spread of 196 per cent between the two ends, which for this occupation is decided mainly by years in the role and by the employer rather than by job title. On the median salary, federal income tax takes about $15,378 and FICA another $8,264, leaving $84,378 in a state with no income tax such as Texas or Florida; add California income tax of roughly $6,183 and take-home pay falls to about $78,195, an effective rate of 27.6 per cent. Education: The typical path to becoming a Data Scientist involves earning a Master's or PhD in Statistics, Computer Science, Mathematics, or quantitative field.
From entry to lead, pay for a Data Scientist roughly 2.2-doubles, running from $70,213 to $155,549. That is the ordinary shape for a skilled occupation: enough room that experience is paid for, not enough that a late start is unrecoverable. The useful comparison when weighing an offer is therefore not against the median but against the band for the level being offered.
The largest single step is the one out of the entry level, worth about $37,807 a year. That places the decisive moment early: the two or three years it takes to stop being junior are worth more than any later promotion, which argues for choosing a first employer on what it will teach rather than on what it pays.
The best-paying states for this occupation are split: WA levies no income tax at all while CA, NY does, so two gross offers that look alike do not end alike. On this median salary the state layer alone is worth several thousand dollars a year, which is why the table below ranks by take-home pay rather than by gross.
Demand concentrates in San Francisco, CA, New York, NY, Seattle, WA, and those are also among the most expensive places to live in the country. A premium of ten or twenty per cent on the median does not survive a housing cost twice the national figure, so the right comparison for a Data Scientist weighing a move is take-home pay minus rent, not salary against salary.
The Data Scientist is one of the most important roles in the Technology sector of the US economy in 2026. With a median annual salary of $108,020, compensation for this position ranges from $62,400 at the entry level to $184,800 for highly experienced professionals in top-paying markets.
This career typically requires Master's or PhD in Statistics, Computer Science, Mathematics, or quantitative field. Valued professional credentials include IBM Data Science Professional, Google Data Analytics Certificate, SAS Certified Data Scientist. On a day-to-day basis, professionals in this role focus on extracting insights from large datasets, building predictive models, designing A/B tests, communicating findings to stakeholders, developing machine learning pipelines, creating dashboards and visualizations, and collaborating with product teams on data-driven features.
The job market for this position shows 35% from 2022-2032 (one of the fastest-growing occupations in the US economy) growth, with demand strongest in specializations including NLP, computer vision, recommendation systems, time-series forecasting, causal inference, and experimentation platforms. Generative AI is creating new opportunities for data scientists to build and fine-tune LLMs, though basic analytics tasks are becoming automated
Salary Range: The typical Data Scientist in the US earns between $62,400 and $184,800 per year, with a median of $108,020.
What Does a Data Scientist Do?
A Data Scientist spends their workday extracting insights from large datasets, building predictive models, designing A/B tests, communicating findings to stakeholders, developing machine learning pipelines, creating dashboards and visualizations, and collaborating with product teams on data-driven features. The role requires proficiency with industry-standard tools and technologies including Python (pandas, scikit-learn, TensorFlow), R, SQL, Spark, Jupyter notebooks, Tableau, cloud ML platforms (SageMaker, Vertex AI).
The typical work environment involves corporate analytics departments, tech companies, consulting firms, or research labs; primarily remote-friendly roles. Within the profession, you can specialize in areas such as NLP, computer vision, recommendation systems, time-series forecasting, causal inference, and experimentation platforms, each requiring different skill sets and offering different compensation levels.
Day-to-day responsibilities vary based on seniority and organization size. Entry-level professionals often focus on execution tasks under supervision, while senior professionals take on strategic planning, mentoring, and cross-functional leadership.
Data Scientist Salary by Experience
| Level | Salary | Hourly | Take-Home |
|---|---|---|---|
| Entry | $70,213 | $34/hr | $55,066 |
| Mid | $108,020 | $52/hr | $78,195 |
| Senior | $135,025 | $65/hr | $94,348 |
| Lead | $155,549 | $75/hr | $106,467 |
Best and Worst States for Data Scientist Pay
Which states let a Data Scientist keep the most, and least, of their salary, ranked by annual take-home pay.
Geographic location significantly impacts Data Scientist compensation. The top-paying states for this role include California (tech company concentration), Washington (cloud/AI research), New York (finance/advertising analytics), Massachusetts (biotech data science), Virginia (government/defense analytics).
States with no income tax (Texas, Florida, Washington, Nevada, Tennessee) offer an effective pay boost of 3-9% compared to high-tax states like California or New York, though these states often compensate with higher cost of living or property taxes. When evaluating offers, consider both gross salary and after-tax take-home pay.
The state-by-state analysis for a Data Scientist at $108,020 reveals that tax geography matters as much as salary negotiation. The $6,183 spread between Texas ($84,378 net) and California ($78,195 net) equals approximately $515 per month in additional disposable income. Over a 10-year career period, this location choice alone represents $61,835 in cumulative wealth difference.
Cost-of-Living Adjusted Analysis: When factoring in regional cost of living, Texas offers the best purchasing power for a Data Scientist salary. While high-tax states like California and New York offer robust Technology job markets, their combined tax burden and cost of living can reduce effective purchasing power by 25-40% compared to states like Texas or Georgia. A Data Scientist earning $108,020 in Texas enjoys purchasing power equivalent to approximately $90,729 in a baseline cost area.
Tech Hub Comparison: Data Scientist roles cluster in San Francisco (highest gross pay but 13.3% state tax), Seattle (strong pay, no state income tax), Austin (growing hub, no state tax), and New York (high compensation offset by 6-10% state/city tax). For remote-capable Data Scientist positions, living in a no-tax state while accessing these markets' salary levels creates optimal after-tax outcomes. A Data Scientist earning Bay Area wages while living in Nevada or Washington state can net $5,401 to $10,802 more annually than California-based peers.
Top 10 Best States for Data Scientist Salary
| # | State | Gross | Federal | State Tax | FICA | Take-Home | Rate |
|---|---|---|---|---|---|---|---|
| 1 | Alaska | $108,020 | $15,378 | $0 | $8,264 | $84,378 | 21.9% |
| 2 | Florida | $108,020 | $15,378 | $0 | $8,264 | $84,378 | 21.9% |
| 3 | Nevada | $108,020 | $15,378 | $0 | $8,264 | $84,378 | 21.9% |
| 4 | New Hampshire | $108,020 | $15,378 | $0 | $8,264 | $84,378 | 21.9% |
| 5 | South Dakota | $108,020 | $15,378 | $0 | $8,264 | $84,378 | 21.9% |
| 6 | Tennessee | $108,020 | $15,378 | $0 | $8,264 | $84,378 | 21.9% |
| 7 | Texas | $108,020 | $15,378 | $0 | $8,264 | $84,378 | 21.9% |
| 8 | Washington | $108,020 | $15,378 | $0 | $8,264 | $84,378 | 21.9% |
| 9 | Wyoming | $108,020 | $15,378 | $0 | $8,264 | $84,378 | 21.9% |
| 10 | North Dakota | $108,020 | $15,378 | $1,822 | $8,264 | $82,556 | 23.6% |
Bottom 10 Worst States for Data Scientist Salary
| # | State | Gross | Federal | State Tax | FICA | Take-Home | Rate |
|---|---|---|---|---|---|---|---|
| 42 | Kansas | $108,020 | $15,378 | $5,500 | $8,264 | $78,878 | 27.0% |
| 43 | Virginia | $108,020 | $15,378 | $5,695 | $8,264 | $78,683 | 27.2% |
| 44 | New York | $108,020 | $15,378 | $5,715 | $8,264 | $78,663 | 27.2% |
| 45 | Minnesota | $108,020 | $15,378 | $5,895 | $8,264 | $78,483 | 27.3% |
| 46 | Delaware | $108,020 | $15,378 | $5,898 | $8,264 | $78,480 | 27.3% |
| 47 | California | $108,020 | $15,378 | $6,183 | $8,264 | $78,195 | 27.6% |
| 48 | Maine | $108,020 | $15,378 | $6,186 | $8,264 | $78,192 | 27.6% |
| 49 | District of Columbia | $108,020 | $15,378 | $6,341 | $8,264 | $78,037 | 27.8% |
| 50 | Hawaii | $108,020 | $15,378 | $7,984 | $8,264 | $76,394 | 29.3% |
| 51 | Oregon | $108,020 | $15,378 | $8,927 | $8,264 | $75,452 | 30.2% |
Data Scientist Take-Home Pay by City
San Francisco leads at $140K+ median; Seattle offers strong AWS/Azure ML roles; New York pays premiums for quantitative finance data science
When comparing city compensation, factor in cost of living differences. A $108,020 salary in a mid-cost city often provides more purchasing power than a 20-30% premium in San Francisco or New York.
How to turn these figures into an actual offer, what to ask for besides base pay and when to name a number, is covered in the guide to negotiating a salary offer.
| City | Gross Salary | Total Tax | Take-Home | Rate |
|---|---|---|---|---|
| San Francisco, CA | $108,020 | $29,825 | $78,195 | 27.6% |
| New York, NY | $108,020 | $29,357 | $78,663 | 27.2% |
| Seattle, WA | $108,020 | $23,642 | $84,378 | 21.9% |
| Boston, MA | $108,020 | $28,823 | $79,197 | 26.7% |
| Washington, DC | $108,020 | $29,983 | $78,037 | 27.8% |
Calculate Data Scientist Take-Home Pay
Adjust the state and filing status to see your estimated after-tax income.
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How to Become a Data Scientist
Education: The typical path to becoming a Data Scientist involves earning a Master's or PhD in Statistics, Computer Science, Mathematics, or quantitative field. Some professionals enter the field through alternative pathways, but formal education provides the strongest foundation for long-term career growth.
Certifications: Key professional credentials for this role include IBM Data Science Professional, Google Data Analytics Certificate, SAS Certified Data Scientist. These certifications demonstrate expertise to employers and often directly correlate with higher compensation.
Skills & Tools: Proficiency with Python (pandas, scikit-learn, TensorFlow), R, SQL, Spark, Jupyter notebooks, Tableau, cloud ML platforms (SageMaker, Vertex AI) is expected for competitive candidates. Building a portfolio of work or gaining practical experience through internships, projects, or entry-level positions is essential for breaking into the field.
Timeline: Most professionals reach mid-level competency within 3-5 years of entering the field, with senior positions typically requiring 7-12 years of progressive experience.
Data Scientist Career Outlook
Employment for the Data Scientist role is projected to grow 35% from 2022-2032 (one of the fastest-growing occupations in the US economy), reflecting strong demand driven by industry evolution and changing workforce needs. The most in-demand specializations include NLP, computer vision, recommendation systems, time-series forecasting, causal inference, and experimentation platforms.
AI and Automation Impact: Generative AI is creating new opportunities for data scientists to build and fine-tune LLMs, though basic analytics tasks are becoming automated
Professionals who combine deep technical expertise with strong communication skills and adaptability will find the best opportunities in this evolving landscape.
The Data Scientist sits in the middle of its adjacent group. Machine Learning Engineer pays $146,100, $38,080 more, while Data Analyst pays $73,500, $34,520 less, against this role's $108,020. A position in the middle is the most flexible one: it means both directions are open, and that the decision rests on what the work is rather than on what the next title pays, since the difference in either direction is a matter of thousands and not of multiples.
After tax the picture compresses. In California, this role's median leaves about $78,195, and across the whole adjacent group the spread between the highest and lowest take-home figure is $43,772 a year. That compression is the progressive schedule at work: a gross gap of ten thousand dollars between two neighbouring occupations is worth appreciably less once the marginal rate has taken its share, which is why a move made for the salary alone disappoints more often than the gross figures suggest.
Tax Tips for Data Scientist Earnings
The strategies that apply to every salaried professional, the contribution limits, the bracket arithmetic and the question of moving to a state without an income tax, are set out once in the guide to tax strategies for salaried professionals rather than repeated on each occupation page.
Data Scientist Salary FAQ
The median annual salary for a Data Scientist in the United States is $108,020 in 2026. Compensation typically ranges from $62,400 for entry-level positions to $184,800 for experienced professionals in top-paying markets. Actual pay depends on experience, location, certifications, and employer size. On a median salary of $108,020, take-home pay works out to about $78,195 a year before state-specific credits.
On a $108,020 salary, a Data Scientist takes home approximately $85,000-$105,000 after federal, state, and FICA taxes, depending on the state and filing status. In no-income-tax states like Texas or Florida, take-home pay is higher than in states like California or New York. On a median salary of $108,020, take-home pay works out to about $78,195 a year before state-specific credits.
Entry-level Data Scientist professionals with 0-2 years of experience can expect to earn around $70,213 per year. Starting salaries vary significantly by location, with major metro areas offering 15-30% premiums over rural areas. On a median salary of $108,020, take-home pay works out to about $78,195 a year before state-specific credits.
The highest-paying states for Data Scientist professionals include CA, WA, NY. However, when adjusted for cost of living, some mid-tier states offer better purchasing power. No-income-tax states provide an additional 3-9% effective pay boost. On a median salary of $108,020, take-home pay works out to about $78,195 a year before state-specific credits.
The median hourly equivalent for a Data Scientist is approximately $51.93, based on 2,080 working hours per year. Actual hourly rates vary by experience level, with senior professionals earning $10-30 more per hour than entry-level. On a median salary of $108,020, take-home pay works out to about $78,195 a year before state-specific credits.
To become a Data Scientist, you typically need Master's or PhD in Statistics, Computer Science, Mathematics, or quantitative field. Valuable certifications include IBM Data Science Professional, Google Data Analytics Certificate, SAS Certified Data Scientist. Most employers also value practical experience gained through internships or entry-level positions.
Employment for Data Scientist professionals is projected to grow 35% from 2022-2032 (one of the fastest-growing occupations in the US economy). Generative AI is creating new opportunities for data scientists to build and fine-tune LLMs, though basic analytics tasks are becoming automated. The strongest opportunities are in NLP, computer vision, recommendation systems, time-series forecasting, causal inference, and experimentation platforms.
A Data Scientist typically spends their day extracting insights from large datasets, building predictive models, designing A/B tests, communicating findings to stakeholders, developing machine learning pipelines, creating dashboards and visualizations, and collaborating with product teams on data-driven features. The work environment involves corporate analytics departments, tech companies, consulting firms, or research labs; primarily remote-friendly roles.
Personal finance and taxation expert. Specialized in US federal and state tax calculations, paycheck analysis, and helping Americans understand their take-home pay across all 50 states.
Sources & References
Tax rates, salary data, and deduction figures used on this page are sourced from official US government publications:
- IRS.gov, Federal income tax brackets, standard deductions, and tax procedures for the 2026 tax year
- Bureau of Labor Statistics (BLS.gov), Occupational Employment and Wage Statistics (OEWS) for median salary data
- Social Security Administration (SSA.gov), Social Security wage base, FICA tax rates, and Medicare thresholds
- IRS Tax Withholding Estimator, Federal paycheck withholding calculations and verification
Last reviewed and updated: 2026-09-27. This content is for informational purposes only and does not constitute tax advice.