Data science sits at the intersection of statistics, programming, and business strategy—and compensation reflects that rare combination. Here’s what data scientists earn by experience, industry, and location in 2026.

Pay at a Glance (BLS Data)

Bureau of Labor Statistics wage estimates for data scientists, across all industries:

Percentile Annual Wage Hourly Equivalent
10th (entry level) $67,240 $32.33
25th $85,660 $41.18
50th (median) $120,230 $57.80
75th $158,880 $76.38
90th $199,130 $95.74
Average (mean) $126,800 $60.96

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics, May 2025, for Data Scientists (all industries). Hourly figures are annual wages divided by 2,080 hours. “Not published” means BLS withheld the estimate, usually because wages are above its top reporting limit.

Data Scientist Salary by Experience Level

Level Years Experience Base Salary Total Comp (Tech) Total Comp (Finance/Consulting)
Entry-level 0-2 $75,000-$95,000 $100,000-$150,000 $85,000-$130,000
Mid-level 2-5 $95,000-$130,000 $150,000-$220,000 $120,000-$180,000
Senior 5-8 $130,000-$170,000 $220,000-$320,000 $160,000-$250,000
Lead/Principal 8-12 $160,000-$210,000 $300,000-$450,000 $200,000-$350,000
Director/VP 12+ $200,000-$280,000 $400,000-$700,000+ $300,000-$600,000

Data Scientist Salary by Industry

Industry Why Higher/Lower
FAANG/Large tech Scaling advantage; equity adds significantly
Finance / Hedge funds Quant skills command premium
Consulting (MBB, Big 4) Diverse work; ladder promotions
Healthcare / Biotech Growing demand; regulatory complexity
E-commerce / Retail tech High-volume recommendation/pricing work
Startups (Series A-C) Equity upside vs. lower base
Insurance / Financial services Stable; less top-end growth
Government / Academia Lower pay; more job security

Data Scientist Salary by State

Rank State Avg Salary Starting Salary Median Salary
1 Washington $158,040 $79,930 $163,350
2 California $156,000 $77,480 $141,590
3 Maryland $144,080 $77,930 $136,370
4 District of Columbia $142,580 $89,750 $126,490
5 New Jersey $138,590 $80,720 $135,280
6 New York $137,690 $73,330 $130,460
7 Massachusetts $136,460 $81,030 $131,750
8 Virginia $134,590 $76,420 $126,430
9 Oregon $131,300 $78,110 $125,990
10 Connecticut $129,850 $75,700 $126,340
11 Colorado $126,800 $74,470 $117,400
12 Minnesota $126,290 $65,730 $128,800
13 Vermont $123,640 $76,570 $127,070
14 North Carolina $121,270 $65,970 $119,090
15 Texas $119,710 $64,540 $122,090
16 Florida $119,150 $63,080 $115,820
17 Hawaii $118,940 $77,270 $102,130
18 Illinois $117,870 $68,810 $106,560
19 Wisconsin $116,600 $76,300 $106,680
20 Arkansas $116,320 $67,090 $109,390
21 Georgia $115,940 $67,750 $104,340
22 Utah $114,880 $60,680 $108,090
23 Arizona $111,950 $65,200 $107,240
24 Rhode Island $111,260 $75,310 $102,440
25 Pennsylvania $110,810 $63,340 $106,850
26 Idaho $110,220 $63,980 $89,380
27 New Hampshire $109,880 $73,480 $100,620
28 Nevada $108,340 $57,150 $98,540
29 Montana $108,170 $67,120 $100,490
30 Ohio $107,160 $61,710 $102,630
31 Michigan $105,890 $60,830 $100,590
32 Tennessee $105,200 $60,200 $100,330
33 Alabama $105,180 $59,130 $103,120
34 Kansas $105,080 $60,520 $98,130
35 South Carolina $102,830 $61,600 $91,990
36 South Dakota $102,450 $67,510 $96,150
37 Missouri $100,880 $58,960 $97,090
38 Kentucky $100,840 $61,990 $91,760
39 Nebraska $98,980 $66,230 $98,230
40 Indiana $98,340 $58,750 $91,470
41 Iowa $98,100 $56,070 $95,830
42 Maine $97,500 $60,280 $90,880
43 Oklahoma $94,950 $58,690 $86,310
44 New Mexico $94,160 $49,990 $95,850
45 West Virginia $90,730 $57,500 $85,090
46 Alaska $89,810 $51,550 $84,110
47 Louisiana $88,480 $53,050 $78,760
48 North Dakota $87,570 $59,030 $81,900
49 Mississippi $79,290 $43,940 $69,490
— National $126,800 $67,240 $120,230

Source: US Bureau of Labor Statistics OEWS, 2025 estimates, fetched 2026-09-29. Figures cover Data Scientists (cross-industry). Some states are omitted where BLS did not publish a reliable estimate.

Role Median Salary Primary Skills Career Path
Data Scientist $108,000 Statistics, ML, Python DS II → Senior → Principal
Data Analyst $72,000 SQL, Excel, visualization Analyst → Senior → Manager
ML Engineer $130,000 ML systems, deployment MLE → Senior → Staff
Data Engineer $115,000 Pipelines, infrastructure DE → Senior → Architect
Business Intelligence $85,000 Dashboards, reporting BI → Senior → Manager

Data science and ML engineering have converged significantly—many senior DS roles now require production deployment skills traditionally held by engineers.

Skills That Increase Pay

Skill Salary Premium
Machine learning / deep learning +15-30%
LLM/GenAI implementation +20-40% (2025-2026 premium)
MLOps / model deployment +15-25%
Causal inference / A/B testing +10-20%
Distributed computing (Spark, BigQuery) +10-20%
Domain expertise (fintech, biotech, etc.) +10-25%
Research publications / PhD +10-15% at research orgs

Education and Certifications

Credential Pay Impact
BS in CS/Statistics/Math Entry qualification; median start
MS in Data Science/Statistics $10,000-$25,000 premium over BS
PhD Research lab or quant finance; top-end premium
Google/AWS ML certifications Modest signal; less than degree
Kaggle competitions Portfolio signal; helps entry-level

Graduate degrees matter more in data science than in software engineering—statistics depth and research experience differentiate senior practitioners.

Maximizing Your Data Scientist Income

Strategy Expected Impact
Move to FAANG / top tech 50-100% total comp increase vs. non-tech
Develop ML engineering skills (not just modeling) Move to higher-paying MLE track
Build domain expertise in high-value vertical +10-25% in finance, health tech
Negotiate offers using competing offers +10-20% on initial offer
Specialize in AI/LLM applications Top premium in current market
Consider quant finance if math-inclined Base salary comparable; bonus significant

See every profession in our salary by profession guides.

Data scientist salaries are tracked in the profession salary guides hub. Compare earnings with the analyst-level role in the data analyst salary guide, and benchmark against national pay ranges at the good salary hub.

Is It a Good Career?

Poor fit for

  • Math/stats averse — Core skills require quantitative comfort.
  • People who hate ambiguity — Business problems are rarely well-defined.
  • Perfectionists — Real data is always messy and imperfect.
  • Those preferring defined tasks — DS requires self-direction and scoping.
  • Non-coders — Python proficiency is non-negotiable.
  • Those wanting guaranteed outcomes — Many models fail, projects get cancelled.
  • Career changers without tech background — Better to start as data analyst first.
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