About WageDex, Bureau of Labor Statistics Salary Data for 800+ Occupations

Our Mission

WageDex makes government salary data accessible and easy to understand. We believe everyone deserves transparent, reliable wage information, whether you're negotiating a raise, planning a career change, or researching labor market trends.

Why we built WageDex: the Bureau of Labor Statistics publishes some of the most comprehensive wage data in the world, yet accessing it requires navigating dense spreadsheets, understanding SOC codes, and piecing together data from multiple downloads. Our purpose is to bridge the gap between raw government statistics and the everyday decisions that workers, students, and employers make about compensation.

We believe salary transparency benefits everyone. When workers understand what their occupation pays across regions and experience levels, they can make more informed career and relocation decisions. When employers understand the competitive landscape, they can offer fairer compensation. WageDex exists to make that transparency effortless.

Our Data Sources

All salary data on WageDex comes from the U.S. Bureau of Labor Statistics Occupational Employment and Wage Statistics (OEWS) survey, the most comprehensive source of occupation-level wage data in the country.

The OEWS survey covers over 1.1 million establishments and produces employment and wage estimates for more than 800 detailed occupations across all 50 states and U.S. territories. The data source includes national, state, and metropolitan-area estimates for each occupation.

Unlike self-reported salary data found on many websites, BLS figures reflect what employers actually pay, collected through mandatory surveys with legal requirements for accuracy. This means the numbers you see here are statistically sound, verifiable, and representative of actual labor market conditions. We also incorporate BLS Occupational Outlook Handbook data for employment projections and career context, as well as regional price parities from the Bureau of Economic Analysis to help users understand cost-of-living differences across geographies.

How We Process the Data

Our methodology begins with downloading the annual BLS Occupational Employment and Wage Statistics survey results, covering over 1.1 million establishments, and organizing them into occupation and geographic profiles. Each profile preserves the full wage distribution (10th, 25th, 50th, 75th, and 90th percentile) plus hourly and annual rates as reported by BLS.

We parse the raw BLS CSV files, normalize occupation titles against the Standard Occupational Classification (SOC) system, and build indexed profiles that link each occupation to its national averages, state-level breakdowns, and metropolitan area variations. The data processing pipeline validates every record against BLS reporting standards and flags suppressed values rather than estimating them.

State and metro-level wage variations let users compare compensation across geographies for the same occupation. Where BLS suppresses wage data due to disclosure standards, typically for occupations with very few workers in a given area, we display it as unavailable rather than estimating a value. We never interpolate, extrapolate, or editorialize BLS figures.

What We Show

Median salary - the midpoint where half of workers earn more and half earn less
Mean (average) salary - total wages divided by total workers
Percentile distribution - 10th, 25th, 75th, and 90th percentiles showing the full range of pay
Employment count - total number of people working in each occupation
Hourly rates - for occupations where hourly wages are more relevant

SOC Classification

Occupations are organized using the Standard Occupational Classification (SOC) system, which groups jobs into 23 major categories, from management and business to production and transportation. Each occupation has a unique SOC code (e.g., 15-1252 for Software Developers). This classification system is maintained by the Bureau of Labor Statistics and is used consistently across all federal statistical agencies.

Data Currency

WageDex currently displays data from the May 2025 OEWS release. The BLS publishes updated wage estimates annually, typically in the spring following the reference period. Our update schedule follows the BLS release calendar, when new estimates become available, we rebuild our database within two weeks of the official release.

Employment outlook projections are sourced from the most recent BLS Occupational Outlook Handbook edition, which covers 2024-2034 employment projections. These projections are updated every two years by BLS. We clearly label the data vintage on every page so users always know how current the information is.

Editorial Independence & How Content Is Produced

WageDex content is compiled by our editorial team from official source data. Raw data from the U.S. Bureau of Labor Statistics (BLS) Occupational Employment and Wage Statistics program is transformed into readable occupation and metro profiles through our continuous editorial pipeline, then validated against the source before publication. The WageDex editorial team, is responsible for editorial standards, methodology, and corrections.

We do not accept payment, sponsorship, or promoted placement from employers, staffing firms, career coaches, or any covered occupation or metro. Our only revenue source is contextual display advertising served by Google AdSense - advertisers do not influence which occupations or areas we cover or how we present wage data, and they do not receive preferential placement.

Limitations and Disclaimers

WageDex is an informational resource, and users should be aware of several important limitations in the underlying data and our presentation of it.

Aggregate statistics do not predict individual outcomes. Salary data should be one factor among many in career and compensation decisions. Individual salaries depend on experience, education, company size, specific location, industry sector, negotiation, and many other factors that aggregate statistics cannot capture. BLS figures represent occupational averages, not guaranteed pay rates.

Suppressed data creates coverage gaps. Some occupations have suppressed wage data (shown as "N/A") where BLS disclosure standards are not met, typically occupations with very few workers in a given area. This means smaller metropolitan areas and less common occupations may have incomplete geographic coverage.

Time lag is inherent in government data. The OEWS data reflects a point-in-time snapshot that is roughly 12-18 months old by the time it is published. Rapidly changing fields (e.g., AI, renewable energy) may show salaries that already differ from current market conditions.

This site is for informational purposes only and does not provide financial, tax, or career advice. Consult a qualified career counselor, financial advisor, or HR professional before making major compensation or career decisions based on this data.

Contact

Questions, corrections, or feedback? We welcome hearing from users, researchers, and journalists. Email us at hello@wagedex.com.

If you notice a data discrepancy or have suggestions for improving WageDex, please include the specific occupation, location, and what appears incorrect. We verify all reports against the original BLS source data.