Also called: AI Auditor, Algorithm Auditor
Tests hiring, lending and other decision-making software from the outside to check whether it treats groups of people unfairly, often because a law requires it.
A company that screens job applicants with software must publish a yearly bias audit under New York City law, so you pull a year of its hiring data and compare pass rates by race and gender. You write up where the tool falls short and meet with the client's lawyers. Next week it's a bank's loan model.
Estimated from data scientist pay and AI-audit firm postings.
Approximate: anchored on Bureau of Labor Statistics data for a broader job group.
Master's degree, about 6 years after high school. Bachelor's in statistics, data science or computer science; a master's is common.
Ways in: 4-year college, Graduate school. Training cost: $60k – $150k.
Majors to look at: Statistics, Data Science, Computer Science, Public Policy.
Growing much faster than average. Driven by laws like NYC Local Law 144 and Colorado's AI Act; still a small field.
Medium risk for 10 years. AI tools speed up the statistics, but deciding what 'fair' means, defending findings and signing reports stays human.
Classes: AP Statistics, Civics or Government, Computer science, Debate.
Official data: O*NET occupation 15-2051.
Career Universe is an early version. Pay, training and AI-risk figures are estimates to start your own research, not verified facts. The research was written with AI research assistants, checked by validation scripts and spot-checked by hand. Check anything important with schools, employers and official sources. How the numbers work.