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
Deliverable
production ML models | dashboards & analysis | research
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
