People Research Scientist, People

Anthropic Anthropic · AI Frontier · San Francisco, CA · People

Research Scientist role focused on organizational science and people analytics within an AI safety company. The role involves designing and executing studies on employee experience, manager effectiveness, and organizational health, utilizing rigorous scientific methods and statistical analysis. It requires expertise in survey design, psychometric methods, and translating research findings into actionable recommendations for people strategy and decision-making. While the company is in AI, the core function of this role is people research, not direct AI/ML model development.

What you'd actually do

  1. Design and execute systematic research studies to answer fundamental questions about employee experience, manager effectiveness, and organizational health
  2. Generate and test hypotheses about people programs, employee behavior, and workforce outcomes using rigorous experimental and quasi-experimental methods
  3. Conduct longitudinal studies tracking employee cohorts to understand long-term workforce trends and the impact of people initiatives
  4. Perform meta-analyses of people interventions across the industry to identify best practices and knowledge gaps
  5. Design, analyze, and iterate on employee listening programs including engagement surveys, pulse surveys, and lifecycle surveys

Skills

Required

  • advanced degree (Master’s or PhD) in I/O Psychology, Organizational Behavior, Statistics, Data Science, Economics, Behavioral Science, or a related research field
  • experimental design
  • hypothesis testing
  • longitudinal research methods
  • causal inference
  • SQL
  • Python/R
  • statistical analysis
  • machine learning
  • survey design
  • psychometric methods
  • employee listening programs
  • data visualization
  • communication skills
  • influence stakeholders

Nice to have

  • 5+ years of experience in research, people analytics, or related quantitative fields
  • people analytics specifically
  • employee engagement or pulse surveys
  • manager effectiveness research
  • organizational science
  • self-service analytics tools or dashboards
  • employee lifecycle metrics
  • people KPIs
  • high-growth technology companies
  • AI/ML organizations
  • network analysis
  • NLP
  • advanced statistical methods
  • BigQuery
  • modern data stack tools
  • Qualtrics
  • Workday

What the JD emphasized

  • track record of challenging assumptions with data and changing long-held practices
  • use data to improve how organizations develop and support their people