Salary Blog

The blog focuses on three areas: occupational deep-dives (how a specific role like AI engineer or registered nurse is paid across the U.S.), methodology explainers (what percentile wages, mean vs. median, and SOC codes actually mean for your job search), and macro shifts in the labor market that show up in BLS data — pay gap movement, skilled trades wage growth, COL-adjusted geographic rankings.

Yes. Every wage figure references the U.S. Bureau of Labor Statistics' Occupational Employment and Wage Statistics (OEWS) program at bls.gov/oes — public domain federal data covering 1.2 million U.S. employers. We do not use estimated or self-reported salary numbers as primary sources.

The current dataset is the 2025 BLS OEWS release, last refreshed May 2026. BLS publishes new OEWS data once per year, typically in spring for the prior survey year. Articles are updated when new data lands or when the underlying SOC classification changes.

Median (50th percentile) is the salary of the worker exactly in the middle of the distribution — half earn more, half earn less. Mean is the simple average across all workers and gets pulled higher by a small number of top earners. Percentiles (10th, 25th, 75th, 90th) show where specific cuts of the distribution sit; the 25th-to-75th band defines the "interquartile" range often used as a salary negotiation anchor.

Private data sources like Glassdoor, Levels.fyi, and Indeed Hiring Lab are useful for granular role-level signal — particularly in tech where total compensation includes equity that BLS does not measure — but they suffer from selection bias (workers who self-report tend to skew toward certain employers and pay levels). We use these as secondary corroboration of the BLS picture, never as primary sources.