People Research Scientist

About the Role

As a People Research Scientist, you will bring deep expertise in research design, measurement, experimentation, and applied data science to OpenAI’s most important People programs. You will design studies, evaluate people processes, and help leaders better empower employees, strengthen organizational systems, and deliver exceptional employee experiences.

This is a high-ownership individual contributor role combining hands-on research, methodological leadership, and scalable people science capabilities. We’re looking for an experienced researcher who can turn ambiguous People questions into rigorous designs, validated insights, and actionable recommendations.

This role is based in San Francisco, CA or Mountain View, CA, with occasional travel to our San Francisco office.

What You’ll Do

• 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 that establish rigorous standards for study design, measurement, validation, and documentation, enabling high-quality, repeatable, and scalable research across the organization.
• Communicate findings through concise, executive-ready narratives.

What We’re Looking For

• Deep curiosity, strong attention to detail, and passion for solving ambiguous and complex problems with creativity.
• Exceptional strength in research design, experimentation, measurement, causal inference, and statistical modeling, including 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 in 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.