About salary.city
Salary numbers lie. A $120k offer in San Francisco and a $90k offer in Austin sound like a $30k difference — but when you factor in housing, taxes, and everyday costs, the Austin offer might actually leave you with more money in your pocket.
salary.city exists to fix this. We combine official Bureau of Labor Statistics (BLS) wage data, U.S. Department of Labor H-1B certified salary disclosures, HUD rent benchmarks and regional cost assumptions to estimate what your salary actually buys in any given city.
What Makes Us Different
Purchasing Power, Not Just Pay
Core metrics combine metro-level cost assumptions, a baseline tax model, and HUD rent benchmarks.
Public Source Discipline
No crowdsourced salary averages. The site prioritizes public sources including BLS OEWS, HUD FMR, and U.S. Department of Labor OFLC disclosures when those signals are shown.
Data Independence
salary.city runs entirely independent data streams. We deliberately ignore subjective "livability" polling metrics to focus on documented compensation math.
Editorial Team & Data Governance
salary.city is maintained by a coalition of remote data journalists and financial engineers.
Our editorial mandate is simple: to decode compensation tradeoffs without pretending that public datasets are more precise than they are. Instead of relying on HR "averages" or self-reported tech salary spreadsheets, our team structures public wage, rent, and tax inputs into comparable scenarios.
By standardizing sources, vintages, and assumptions, our team helps job seekers understand the estimated terms of an offer. We do not accept sponsored data placements.
Editorial Guidelines
Our commitment to Data Neutrality means observed wage inputs and projected scenario values must stay labeled separately. The permutations generated by our engine follow documented assumptions for tax estimates, local cost adjustments, and BLS wage estimates. No crowdsourced averages are treated as public truth.
Editorial Leadership & Data Verification
Eleanor Vance
Senior Compensation Analyst
Eleanor leads the data verification pipeline at salary.city. With a background in statistical arbitrage and corporate total-rewards analysis, she ensures that every cross-referencing model used to derive purchasing power against federal BLS databases reflects true on-the-ground reality, rigorously suppressing anomalies and tracking hyper-local tax implications.