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People Research Data Scientist, AI Fairness & Bias

OpenAI · San Francisco

hybridunknown$198,000–$220,000Posted Aug 31, 2026PythonSQLMachine LearningFairness & Bias TestingStatistical AnalysisAlgorithmic Auditing

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About this role

**People Research Data Scientist, AI Fairness & Bias** **ABOUT THE TEAM** OpenAI's People team hires, engages, and retains world-class talent to safely build and deploy AGI that benefits all of humanity. The People Analytics team helps leaders make rigorous, evidence-based talent decisions and ensures that the systems supporting those decisions are valid, reliable, fair, and accountable. **ABOUT THE ROLE** As a People Data Scientist focused on AI fairness and bias testing, you will help establish how OpenAI evaluates AI-assisted People systems and high-impact talent processes. You will design and conduct rigorous assessments to identify, measure, and mitigate potential bias across the lifecycle of models, agents, decision-support tools, and automated workflows. **KEY RESPONSIBILITIES** • Define and lead fairness and bias-testing strategies for AI-assisted People processes • Design rigorous algorithmic audits and validation studies • Identify appropriate fairness criteria and evaluate tradeoffs • Evaluate end-to-end human-AI decision systems • Develop evaluation approaches for generative and agentic AI • Investigate sources of observed disparities • Partner with engineering, People Operations, Legal, and Privacy teams • Build scalable fairness-evaluation infrastructure • Establish research and documentation standards • Translate complex findings into decision-ready narratives **REQUIRED QUALIFICATIONS** • Deep expertise in algorithmic fairness, bias measurement, or responsible AI • Exceptional strength in research design and statistical modeling • Hands-on experience with subgroup analysis, adverse-impact testing, and validation studies • Strong judgment about fairness metrics limitations • Experience evaluating ML models and human-AI workflows • High proficiency in Python/R and SQL • Experience building reproducible evaluation pipelines • Ability to communicate findings with technical and executive stakeholders **PREFERRED QUALIFICATIONS** • Experience conducting fairness assessments in employment or high-impact domains • Familiarity with Fairlearn, AI Fairness 360, or comparable tools • Experience evaluating LLMs and generative AI systems • Background in employment selection or talent assessment • Advanced degree in Quantitative Psychology, Computer Science, Statistics, or related field (PhD preferred) **LOCATION** San Francisco, CA (preferred) *OpenAI is an equal opportunity employer. For more information, see our EEO Policy Statement.*

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