People Research Data Scientist, AI Fairness & Bias

Highlights

• Lead fairness and bias testing for AI-assisted hiring and talent systems.
• Audit generative and agentic AI for disparate outcomes and risks.
• Build scalable fairness evaluation pipelines and monitoring tools.

What they offer

• Equity

Ideal candidate

An experienced applied researcher passionate about equitable AI who combines rigorous measurement judgment with curiosity, humility, and care for building talent systems that work for everyone.

Requirements

• Deep expertise in algorithmic fairness, bias measurement, responsible AI, psychometrics or high-impact decision systems
• Strength in research design, measurement, experimentation, causal inference and statistical modeling
• Hands-on experience with subgroup and intersectional analysis, adverse-impact testing and validation studies
• High proficiency in Python or R and SQL with complex, sensitive datasets
• Experience building reproducible evaluation pipelines, testing frameworks and monitoring systems
• Ability to partner with technical, legal, privacy and executive stakeholders