People Research Scientist
OpenAIGenerative AI company
San Francisco, United StatesSenior
Microsoft
Nvidia
Thrive Capital
Sequoia Capital
SoftBank
Amazon
People / HR / RecruitmentNew
About the role
TL;DR
Design and evaluate people programs using research and data science.
- •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.
- •Key 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 that establish rigorous standards for study design, measurement, validation, and documentation, enabling high-quality, repeatable, and scalable research across the organization.
- •Requirements 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.
Required skills
RPythonSQLA/B Testing
Nice-to-have skills
MLflowKubeflowSageMakerVertex AIONNXJAXLangChainHugging FaceComputer VisionNLP
Domain expertise
aiproductivity
Tech stack
RPythonSQLGitLinuxJiraConfluenceExcelPowerPoint