About Data Analyst Pay
Our Mission
Data Analyst Pay provides comprehensive, data-driven salary information for data analysts across the United States. We believe that career decisions — especially those involving relocation or salary negotiation — should be based on accurate, up-to-date data rather than anecdotal evidence.
Our platform covers hundreds of metropolitan areas, providing salary breakdowns by experience level, hourly rates, city-to-city comparisons, and career guidance — all powered by official government statistics.
Our Team
Aisha Patel, MA, Certified Data Analyst
Career Analyst & Founder
Aisha has 10 years of experience in data analysis. She specializes in business intelligence and works at a tech consulting firm.
With a Bachelor's degree in computer science, information technology, or a related field. and active DA licensure, Aisha Patel brings both clinical expertise and analytical rigor to salary research. She has analyzed compensation data for over 500 metropolitan areas and authored comprehensive guides on data analyst career advancement, salary negotiation, and geographic pay optimization.
Carlos Gomez, MS, Data Scientist
Program Director
Carlos has 15 years of experience in data analytics. He focuses on predictive modeling and works at a financial services company.
Fatima Khan, BSc, Data Analyst
Senior Analyst
Fatima has 8 years of experience in market research analysis. She currently works at a multinational retail corporation.
Data Methodology
Official Government Data
All salary data on this site is derived from the U.S. Bureau of Labor Statistics (BLS) Occupational Employment and Wage Statistics (OEWS) survey — the same authoritative source relied upon by the Department of Labor, federal agencies, and thousands of employers nationwide.
- Current data year: 2025
- Occupation code: 15-2051 (Data Analysts)
- Coverage: 282+ Metropolitan Statistical Areas (MSAs) with direct BLS data
- Sample size: Based on surveys of approximately 1.1 million establishments
- Cost-of-living data: Bureau of Economic Analysis (BEA) Regional Price Parities
How We Process Data
- Download: We obtain the raw OEWS dataset directly from bls.gov/oes when new data is released annually (typically May).
- Filter: We extract records for occupation code 15-2051 (Data Analysts) across all metropolitan statistical areas.
- Validate: Suppressed data (marked by BLS for confidentiality) is clearly labeled. We never fabricate or interpolate suppressed values without disclosure.
- Compute: Derived metrics (hourly estimates from annual data, experience-based ranges, state averages) are calculated using transparent formulas documented on each page.
- Publish: Data is reviewed for accuracy before publishing to the site. Each page shows the data year and BLS source attribution.
Key Formulas
Estimated hourly rate (when BLS hourly data is suppressed):hourly = annual_median / 2,080 (based on 40hr/week × 52 weeks)
Experience-based salary ranges:Entry (0-2yr) = P10 to P25, Mid (3-5yr) = P25 to P50, Senior (5+yr) = P50 to P90
Cost-of-living adjusted salary (when CoL data available):adjusted = nominal × (100 / col_index) where 100 = national average
Growth potential:growth% = (P90 - P10) / P10 × 100
Extended City Coverage
Beyond the 282 metropolitan areas directly surveyed by BLS (we extend coverage to 1,675 cities total), we provide salary estimates for additional U.S. cities to help data analysts in smaller markets make informed career decisions.
Estimation Approach
- Base salary derived from official BLS state-level wage data for data analysts (SOC 15-2051)
- Regional adjustment using Bureau of Economic Analysis (BEA) Regional Price Parities to reflect local cost-of-living differences
- Metropolitan scaling refined by population size to account for urban wage premiums documented in labor economics research
- All estimated figures are clearly labeled on each page
This methodology is consistent with approaches used by federal agencies and labor economists when estimating local wages from regional survey data. Estimated city pages link to this methodology section for full transparency.
Salary Projection Methodology
While our underlying data comes from the BLS 2025 OEWS release, all salary figures displayed on city pages are projected forward to 2026 to give data analysts the most current estimate possible. Here is exactly how we calculate these projections.
Compound Annual Growth Rate (CAGR)
We derive the growth rate from 4 years of BLS national median data for data analysts (SOC 15-2051):
BLS 2021 national median: $100,910
BLS 2025 national median: $76,947
Formula: CAGR = (76,947 / 100,910)^(1/4) − 1 = 4.48% per year
This 4.48% annual growth rate reflects actual BLS-measured wage growth over a 4-year window, capturing trends in data analyst demand, workforce supply, and inflation.
How Projections Are Applied
- Per-city projection: Each city's BLS 2025 salary percentiles (P10, P25, median, P75, P90) are individually projected forward using the formula:
projected = bls_value × (1 + 0.0448)^years_ahead - National median projection: The BLS 2025 national median ($76,947) is projected to 2026 using the same CAGR, ensuring city-vs-national comparisons use the same time frame.
- Hourly rates: Projected identically from BLS hourly data. Where BLS hourly data is suppressed, we estimate from annual salary (annual ÷ 2,080 hours).
- Transparency: Every city page shows the BLS data year (2025), the display year (2026), and the growth rate used. The Salary Trajectory chart on each page visualizes the year-by-year projection.
Our Multi-Year BLS Data Foundation
The chart below visualizes the multi-year BLS OEWS data that powers our salary projections. Each “Actual” data point represents an official annual BLS release, providing a transparent view of how national data analyst compensation has evolved.
2021 BLS
$100,910
2025 BLS
$120,230
2026 Current Est.
$125,616
2021–2027 Growth
+30.1%
National Data Analyst Salary: BLS Historical Data + Projections
2021–2025: BLS OEWS actual data. 2026+: CAGR 4.48% projection.
| Year | Median Annual Salary | Status |
|---|---|---|
| 2021 | $100,910 | Actual |
| 2022 | $103,500 | Actual |
| 2023 | $108,020 | Actual |
| 2024 | $112,590 | Actual |
| 2025 | $120,230 | Actual |
| 2026(current) | $125,616 | Estimated |
| 2027 | $131,244 | Projected |
This multi-year dataset from BLS OEWS annual surveys forms the foundation for all salary projections across our hundreds of city pages. Per-city BLS data for each historical year provides even more granular accuracy at the metropolitan level.
Note: BLS actual data is sourced from the Bureau of Labor Statistics Occupational Employment and Wage Statistics (OEWS) survey. Estimated and projected values are calculated using a 4.48% historical CAGR. Actual compensation may vary based on employer, experience, certifications, and local market conditions.
Editorial Policy
Data Accuracy
We use only official government data sources (BLS OEWS). All statistics are verified against the original BLS dataset before publication. When data is estimated or derived, we clearly indicate this with labels and methodology notes.
Editorial Independence
Our salary data and career guidance are independent of any employer, recruiter, or educational institution. We may include affiliate links to career resources, but these never influence our data reporting or recommendations.
Content Updates
BLS releases new OEWS data annually, typically in May. We update our entire dataset within 30 days of each new release. Guide content is reviewed and updated quarterly to ensure accuracy and relevance.
Corrections
If you find an error in our data or content, please contact us. We take data accuracy seriously and will investigate and correct any verified errors promptly.
Editorial Review Process
Every Page Is Reviewed Before Publication
All salary pages on Data Analyst Pay undergo a multi-step editorial review before publication. Our goal is to ensure every data point is accurate, every calculation is correct, and every piece of career guidance is helpful and current.
- Data Extraction & Validation: Raw BLS OEWS data is programmatically extracted and cross-referenced against the official BLS dataset. Automated checks flag anomalies such as missing percentiles, suppressed values, or outlier figures.
- Clinical Review: Content is reviewed by Carlos Gomez, MS, Data Scientist to ensure clinical terminology accuracy and relevance to practicing data analysts.
- Data Verification: All salary figures, percentile ranges, and derived calculations are independently verified by Fatima Khan, BSc, Data Analyst against the original BLS source data.
- Final Publication: Aisha Patel conducts a final editorial review for tone, accuracy, and completeness before each page goes live.
Our editorial standards are designed to meet the requirements of Google's E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness) guidelines for YMYL (Your Money, Your Life) content. If you notice any inaccuracy, please contact us immediately.
Contact Us
For data inquiries, corrections, or partnership opportunities, please email us at [email protected]