O

Hybrid

People Research Scientist

OpenAI

Overview

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.

Benefits, from the posting itself

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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.

Key Requirements

  • Deep curiosity, strong attention to detail, and passion for solving ambiguous and complex problems with creativity.
  • 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.