Historical composite score tracking labor market conditions for job seekers. Higher scores indicate better conditions for finding new employment.
Giving job seekers the same market intelligence employers have. An experiment in AI-assisted pro-worker tooling.
Job market conditions shift before the narrative catches up. By the time "it's a great market" or "hiring is frozen" becomes conventional wisdom, the data has usually been pointing that direction for months.
This dashboard uses eight economic indicators to cut through the noise and give job seekers a clearer, earlier read on conditions. The score runs from 0 to 100 — higher means better for workers. Data comes from the Bureau of Labor Statistics and Federal Reserve, updated monthly.
Start with the score, then explore what's driving it, then see what would need to change.
This tracks the US labor market overall. Tech can freeze 18 months before it shows in national data; healthcare and government often move on different cycles entirely. If your sector feels worse than the score suggests, trust your network over the number.
Historical composite score tracking labor market conditions for job seekers. Higher scores indicate better conditions for finding new employment.
The score combines eight labor market indicators, weighted by how directly they measure worker leverage:
The score also applies adjustments for unusual conditions: when the job openings ratio falls below 1.0 (more seekers than jobs), when the market is "frozen" (low hiring AND low quitting), and when Fed rates are near zero (historically stimulative).
Score = (0.6 × CoreAvg + 0.4 × ContextAvg) × 100 × adjustments
Each metric is normalized to 0–1 based on historical ranges (e.g., quit rate: 1.5% = 0, 3.0% = 1). Adjustments: ×0.92 if jobs/seeker < 1.0; up to ×0.88 for frozen market; ×1.08 if Fed rate < 0.5%.
View source code →This is national data. Your industry, region, and role may differ significantly. Tech hiring can freeze while healthcare booms. San Francisco and rural Ohio are different markets.
The data lags reality. BLS releases come 4-6 weeks after the reference month. By the time you see it here, conditions may have shifted.
The thresholds are calibrated to recent history. A "bad" quit rate today might have been normal in 2010. The score tells you how now compares to 2015-2025, not to all of history.
There's no confidence interval. The score of "47" should really be read as "somewhere around 45-50" given measurement uncertainty and model choices.
All data comes from official government sources, retrieved via the Federal Reserve Economic Data (FRED) API:
Data updates automatically each month after BLS releases. The code is open source if you want to verify or adapt it.