People Research Scientist

Details

OpenAI’s People Analytics team helps leaders make evidence-based talent decisions. This role applies research design, measurement, experimentation, and applied data science to People programs, including employee experience, organizational health, manager effectiveness, recruiting, and talent outcomes.

The position is a high-ownership individual contributor role combining hands-on research, methodological leadership, and scalable people science capabilities. It is based in San Francisco, California, or Mountain View, California, with occasional travel to the San Francisco office.

Responsibilities

• Design rigorous research and evaluation strategies for recruiting, organizational health, manager effectiveness, employee experience, and talent outcomes.
• Apply advanced statistical modeling, machine learning, and research methods to inform program design, evaluate effectiveness, and quantify business impact.
• Partner with People Operations, data engineering, and people systems teams to define data requirements, improve data quality, establish documentation standards, and ensure research datasets are governed, reproducible, and privacy-preserving.
• Build scalable people science infrastructure, including self-service agentic tools, automated validation workflows, reusable research datasets, and analytical pipelines.
• Develop research playbooks establishing rigorous standards for study design, measurement, validation, and documentation.
• Communicate findings through concise, executive-ready narratives.

Requirements

• Deep curiosity, strong attention to detail, and a passion for solving ambiguous and complex problems creatively.
• Exceptional strength in research design, experimentation, measurement, causal inference, and statistical modeling.
• Hands-on experience with psychometrics, survey methodology, structural equation modeling, multilevel modeling, randomized controlled experiments, A/B testing, quasi-experimental design, validation studies, and machine learning evaluation.
• High proficiency in R or Python and SQL, with experience working across complex, messy datasets.
• Experience building measurement systems, research programs, data products, reusable analytics frameworks, self-service tools, and governed analytical workflows.
• Ability to communicate complex methods and tradeoffs clearly to senior leaders, technical partners, and non-technical audiences.
• Sound judgment when handling sensitive employee data, including privacy, fairness, bias, and responsible research practices.

Preferred Qualifications

• Experience evaluating AI-assisted workflows, algorithmic systems, and human-AI decision processes in operational contexts, including familiarity with model evaluation methods.
• Advanced degree in Industrial-Organizational Psychology, Organizational Behavior, Quantitative Psychology, Behavioral Economics, Statistics, Economics, Data Science, or a related field.

Benefits

• Equity, performance-related bonuses for eligible employees, and comprehensive benefits.
• Medical, dental, and vision insurance, with employer contributions to Health Savings Accounts.
• Pre-tax accounts for health and dependent care expenses, commuting, parking, and transit.
• 401(k) retirement plan with employer match.
• Paid parental, medical, and caregiver leave.
• Paid time off, company holidays, and office closures.
• Mental health and wellness support.
• Employer-paid basic life and disability coverage.
• Annual learning and development stipend.
• Daily office meals and eligible meal delivery credits.
• Relocation support for eligible employees.
• Additional benefits may include charitable donation matching and wellness stipends.