Source: BLS OEWS May 2024
The median annual salary for data scientists in 2024 is $108,660 according to BLS OEWS. By Experience Level: Entry-level (0-2 years): $80,000-$105,000; Mid-level (3-5 years): $100,000-$135,000; Senior (6+ years): $140,000-$180,000+. Total Comp at Big Tech: $180K-$450K+ depending on level and company.
- 1.Median data scientist salary is $108,660/year with 35% job growth projected 2022-2032 (BLS OOH)
- 2.Top-paying metros: San Jose ($164K), Seattle ($142K), San Francisco ($156K) - but high cost of living offsets premium
- 3.35% job growth is much faster than average, adding 17,700 new positions through 2032
- 4.Total compensation at FAANG companies ranges $180K-$450K for data scientists, with Staff level exceeding $500K
- 5.Skills premiums: Machine Learning (+25%), Deep Learning (+30%), Cloud/Big Data (+20%) over baseline
Data Scientist Salary Overview 2025
Data science has emerged as one of the highest-paid tech professions, combining statistical analysis, machine learning, and business insight to drive decision-making across industries. The field offers strong compensation growth as you advance from entry-level analyst roles to senior scientist and principal positions.
This comprehensive salary guide uses data from the Bureau of Labor Statistics OEWS May 2024 for official salary statistics and Levels.fyi for tech company total compensation data. We also analyze salary trends by location, industry, and specialization to give you a complete picture of data scientist earning potential.
For those considering a career transition into data science, explore our data science degree programs or data science bootcamp options.
Data Scientist Salary by Experience Level
| Data Scientist II | 2-4 years | $100,000-$135,000 | $160,000-$240,000 | 35% |
| Entry/Junior Data Scientist | 0-2 years | $80,000-$105,000 | $120,000-$180,000 | 30% |
| Principal Data Scientist | 10+ years | $200,000-$280,000 | $400,000-$600,000 | 3% |
| Senior Data Scientist | 4-7 years | $130,000-$170,000 | $220,000-$320,000 | 25% |
| Staff Data Scientist | 7-10 years | $160,000-$220,000 | $300,000-$450,000 | 7% |
Data Scientist Salary by Location
| # | ||||
|---|---|---|---|---|
| 1 | San Jose-Sunnyvale-Santa Clara, CA | $164,280 | 4,320 | 272 |
| 2 | San Francisco-Oakland-Berkeley, CA | $155,870 | 3,180 | 240 |
| 3 | Seattle-Tacoma-Bellevue, WA | $142,350 | 4,560 | 182 |
| 4 | New York-Newark-Jersey City, NY-NJ | $135,680 | 6,890 | 235 |
| 5 | Boston-Cambridge-Newton, MA-NH | $128,940 | 3,420 | 185 |
| 6 | Washington-Arlington-Alexandria, DC-VA-MD | $126,750 | 4,180 | 164 |
| 7 | Los Angeles-Long Beach-Anaheim, CA | $124,560 | 3,980 | 192 |
| 8 | Austin-Round Rock-Georgetown, TX | $119,850 | 2,340 | 123 |
| 9 | Denver-Aurora-Lakewood, CO | $116,420 | 2,180 | 145 |
| 10 | Chicago-Naperville-Elgin, IL-IN-WI | $112,680 | 3,560 | 126 |
Data Scientist Salary: Cost-of-Living Adjusted
While San Jose offers the highest nominal salaries for data scientists ($164K median), the cost-of-living index of 272 significantly impacts purchasing power. Austin provides excellent value with $119K median salary and much lower living costs (COL index 123).
| Metro Area | Median Salary | COL Index | Adjusted Salary | Net Advantage |
|---|---|---|---|---|
| Austin, TX | $119,850 | 123 | $97,439 equivalent | +$28,439 |
| Denver, CO | $116,420 | 145 | $80,290 equivalent | +$11,290 |
| Seattle, WA | $142,350 | 182 | $78,214 equivalent | +$9,214 |
| Boston, MA | $128,940 | 185 | $69,697 equivalent | Baseline |
| San Jose, CA | $164,280 | 272 | $60,397 equivalent | -$9,300 |
| New York, NY | $135,680 | 235 | $57,736 equivalent | -$11,961 |
Data Scientist Salary by Industry & Company Type
Industry choice significantly impacts data scientist compensation. Technology companies typically offer the highest total compensation, while traditional industries may offer lower base salaries but stronger benefits and work-life balance.
| Industry/Company Type | Entry Level | Senior Level | Staff Level | Key Benefits |
|---|---|---|---|---|
| FAANG (Meta, Google, Amazon, Apple, Netflix) | $140K-$180K TC | $250K-$350K TC | $400K-$550K TC | Stock upside, prestige |
| Top Tech (Microsoft, Uber, Stripe, Airbnb) | $120K-$160K TC | $220K-$320K TC | $350K-$480K TC | Growth potential, innovation |
| Fintech (Goldman, JPM, Citadel) | $130K-$170K | $200K-$280K | $300K-$450K | Bonuses, finance domain |
| Consulting (McKinsey, BCG, Bain) | $120K-$150K | $180K-$250K | $280K-$400K | Travel, diverse projects |
| Healthcare/Pharma | $95K-$125K | $140K-$180K | $200K-$280K | Mission-driven, stability |
| Traditional Enterprise | $85K-$115K | $120K-$160K | $160K-$220K | Work-life balance, benefits |
| Startups (Series A-C) | $90K-$130K + equity | $130K-$180K + equity | $180K-$250K + equity | Equity upside, autonomy |
Data Scientist Total Compensation Breakdown
At major tech companies, total compensation extends far beyond base salary. Understanding each component helps in offer evaluation and negotiation strategy.
| Component | Entry Level | Senior Level | Staff Level | % of Total |
|---|---|---|---|---|
| Base Salary | $110,000 | $165,000 | $220,000 | 40-65% |
| Stock/RSUs (Annual) | $25,000 | $80,000 | $180,000 | 25-45% |
| Annual Bonus | $12,000 | $25,000 | $45,000 | 8-15% |
| Sign-On (Amortized) | $8,000 | $20,000 | $35,000 | 5-8% |
| Benefits | $12,000 | $15,000 | $20,000 | 5-8% |
| **Total Compensation** | **$167,000** | **$305,000** | **$500,000** | 100% |
Top-Paying Companies for Data Scientists
| # | ||||
|---|---|---|---|---|
| 1 | Netflix | $280,000 | $420,000 | $580,000 |
| 2 | Meta | $175,000 | $350,000 | $520,000 |
| 3 | $170,000 | $320,000 | $480,000 | |
| 4 | Apple | $160,000 | $300,000 | $450,000 |
| 5 | Amazon | $155,000 | $280,000 | $420,000 |
| 6 | Stripe | $165,000 | $340,000 | $500,000 |
| 7 | Uber | $150,000 | $290,000 | $440,000 |
| 8 | Microsoft | $145,000 | $270,000 | $400,000 |
| 9 | Airbnb | $160,000 | $310,000 | $470,000 |
| 10 | $150,000 | $285,000 | $430,000 |
| Skill/Specialization | Salary Premium | Demand Level | Related Resources |
|---|---|---|---|
| Deep Learning/Neural Networks | +25-35% | Very High ↑ | [AI/ML Engineering](/careers/ai-ml-engineer-salary/) |
| MLOps/Production ML | +20-30% | Very High ↑ | [Machine Learning Degree](/degrees/machine-learning/) |
| Computer Vision | +20-25% | High ↑ | [AI Degree Programs](/degrees/artificial-intelligence/) |
| NLP/Large Language Models | +18-25% | Very High ↑ | [Data Science Bootcamps](/skills/bootcamps/data-science/) |
| Cloud Platforms (AWS/GCP/Azure) | +15-20% | High ↑ | [AWS Certifications](/skills/aws-certifications-roadmap/) |
| Big Data (Spark, Hadoop) | +12-18% | Stable → | [Data Analytics Degree](/degrees/data-analytics/) |
| Statistics/Econometrics PhD | +15-25% | High → | [Data Science Masters](/degrees/data-science/best-masters-programs/) |
| Python/R Advanced | +8-15% | High → | [Technical Interview Prep](/skills/technical-interview-prep/) |
| SQL/Database Optimization | +5-12% | High → | [Database Management](/degrees/database-management/) |
| Business Intelligence/Tableau | +3-8% | Stable → | [Data Analytics Bootcamps](/skills/bootcamps/data-analytics/) |
Education Impact on Data Scientist Salary
Educational background significantly impacts data scientist starting salaries and career trajectory. While self-taught and bootcamp graduates can succeed, advanced degrees often correlate with higher initial compensation and faster advancement.
| Education Background | Starting Salary | 5-Year Salary | Advancement Speed | Notes |
|---|---|---|---|---|
| PhD (Statistics, CS, Physics) | $110K-$140K | $160K-$220K | Fast | Research roles, principal track |
| Master's Data Science | $95K-$125K | $140K-$180K | Fast | Most common path |
| Master's (Related Field) | $90K-$115K | $130K-$170K | Medium | CS, Math, Engineering |
| Bachelor's + Bootcamp | $85K-$105K | $120K-$160K | Medium | Career switchers |
| Bachelor's STEM | $80K-$100K | $115K-$150K | Medium | Strong foundation |
| Bootcamp Only | $70K-$90K | $105K-$140K | Slow | Portfolio critical |
| Self-Taught | $65K-$85K | $100K-$135K | Slow | Exceptional portfolio needed |
Data Scientist Career Progression & Salary Timeline
Data science career progression typically follows predictable patterns with clear salary milestones. Understanding these pathways helps set realistic expectations and career planning goals.
| Years | Typical Role | Salary Range | Key Milestones | Next Steps |
|---|---|---|---|---|
| 0-2 | Data Analyst/Junior DS | $70K-$100K | Learn tools, build portfolio | Master SQL, Python, basic ML |
| 2-4 | Data Scientist II | $95K-$130K | First ML models in production | Specialize in domain/technology |
| 4-7 | Senior Data Scientist | $125K-$170K | Lead projects, mentor juniors | Technical leadership skills |
| 7-12 | Staff/Principal DS | $160K-$250K | Cross-team impact, strategy | Choose IC vs management |
| 12+ | Distinguished/Director | $200K-$350K+ | Org-wide influence | Executive/research leadership |
Career Paths
Data Engineer
Build data pipelines and infrastructure
Education Paths to Data Science Careers
Multiple educational pathways lead to successful data science careers, each with different time commitments, costs, and outcomes:
- Best Data Science Degree Programs — Comprehensive overview of degree options
- Data Science Bootcamps — Intensive 12-24 week programs with job placement support
- Data Analytics Bootcamps — Shorter programs focused on analytics and visualization
- Computer Science Programs — Strong foundation for ML/AI specialization
- Bootcamp vs Master's Comparison — ROI analysis for career changers
- Self-Taught vs Degree — Honest comparison of pathways
For working professionals, consider part-time options or employer tuition reimbursement programs.
Data Scientist Salary FAQ
Related Salary Guides & Data Science Resources
Salary Data Sources & Methodology
Official government salary data for data scientists (SOC 15-2051), May 2024 survey
Crowdsourced total compensation data from tech companies, verified offers
Job growth projections and education requirements
Annual salary trends report based on platform data
Taylor Rupe
Full-Stack Developer (B.S. Computer Science, B.A. Psychology)
Taylor combines formal training in computer science with a background in human behavior to evaluate complex search, AI, and data-driven topics. His technical review ensures each article reflects current best practices in semantic search, AI systems, and web technology.