SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
OpenAI's People Analytics team is seeking a People Research Scientist to design and execute rigorous research studies that inform talent decisions and organizational effectiveness. This high-ownership individual contributor role combines hands-on research methodology, statistical analysis, and applied data science to evaluate OpenAI's most critical people programs.
You will design rigorous research and evaluation strategies across recruiting, organizational health, manager effectiveness, employee experience, and talent outcomes. Using advanced statistical modeling, machine learning, and research methods, you'll quantify program impact and provide actionable recommendations to senior leaders. You'll partner with People Operations, data engineering, and systems teams to define data requirements, improve data quality, and establish governance standards that ensure research datasets are reproducible and privacy-preserving.
A key part of this role involves building scalable people science infrastructure, including self-service tools, automated validation workflows, reusable research datasets, and analytical pipelines. You'll develop research playbooks that establish rigorous standards for study design, measurement, validation, and documentation, enabling high-quality, repeatable research across the organization.
Required qualifications include deep expertise in research design, experimentation, measurement, and causal inference. You should have hands-on experience with psychometrics, survey methodology, structural equation modeling, multilevel modeling, randomized controlled experiments, A/B testing, quasi-experimental design, and validation studies. High proficiency in R or Python and SQL is essential, along with experience building measurement systems, research programs, data products, and self-service analytics frameworks. You must communicate complex methods clearly to senior leaders and non-technical audiences, and demonstrate sound judgment handling sensitive employee data with attention to privacy, fairness, and bias.
Preferred qualifications include experience evaluating AI-assisted workflows and algorithmic systems in operational contexts, and an advanced degree in Industrial-Organizational Psychology, Organizational Behavior, Quantitative Psychology, Behavioral Economics, Statistics, Economics, Data Science, or related field.
The role is based in San Francisco or Mountain View with occasional travel to the San Francisco office.
