People Research Data Scientist, AI Fairness & Bias
Recruiter Fit Breakdown & Candid Summary
This role is for an experienced applied researcher or data scientist specializing in algorithmic fairness, psychometrics, and high-stakes decision systems.
The ideal candidate bridges the gap between technical model evaluation and organizational talent processes, requiring both statistical rigor and the ability to influence senior leadership.
This is not a generalist data science role; it requires deep expertise in measurement validity, adverse-impact analysis, and the nuances of human-AI interaction.
Candidates without a strong background in formal fairness metrics or psychometric validation are unlikely to be successful.
Role Responsibilities
- 1Define and lead fairness and bias-testing strategies for AI-assisted People processes and decision-support systems.
- 2Design rigorous algorithmic audits, including adverse-impact analysis, subgroup evaluation, and measurement invariance studies.
- 3Evaluate end-to-end human-AI decision systems, analyzing model outputs, user behavior, and human oversight.
- 4Develop scalable fairness-evaluation infrastructure, including automated validation pipelines and reusable datasets.
- 5Partner with cross-functional teams (Legal, Privacy, Engineering) to recommend and implement bias mitigations.
- 6Translate complex research findings into actionable narratives for senior leadership.
Skills Matrix
Must-Have Skills
Nice-to-Have Skills
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