People Research Data Scientist, AI Fairness & Bias
Core
Design and conduct rigorous assessments to identify, measure, and mitigate potential bias in AI-assisted People systems and high-impact talent processes.
Role type
Senior IC data scientist (AI fairness & bias)
Builds
Scalable fairness-evaluation infrastructure, automated validation pipelines, and decision-ready narratives for leaders.
Domain
AI safety, People Analytics, Employment Systems
Required skills
algorithmic fairness, bias measurement, psychometrics, applied statistics, research design, causal inference, statistical modeling, Python, SQL, data quality assessment
Preferred skills
adverse-impact analysis, subgroup and intersectional evaluation, generative AI evaluation, employment selection validation, responsible-AI frameworks
Technologies
Fairlearn, AI Fairness 360, Python, R, SQL
Responsibilities
Define fairness and bias-testing strategies for AI-assisted People processes; Design algorithmic audits and validation studies; Identify appropriate fairness criteria and document limitations; Evaluate end-to-end human-AI decision systems; Develop evaluation approaches for generative and agentic AI; Investigate sources of observed disparities; Partner with teams to recommend mitigations; Build scalable fairness-evaluation infrastructure; Establish research and documentation standards; Translate complex findings into concise narratives.
Seniority
Senior, hands-on IC
