People Research Scientist, Recruiting at Anthropic

Hybrid - New York City, NY; Seattle, WA; San Francisco, CA

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Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. We are seeking a Recruiting Research Scientist to join our People Data Solutions team. You’ll be the research expert supporting our Recruiting organization, using rigorous scientific methods to advance our understanding of recruiting funnels, interview effectiveness, candidate experience, and recruiting capacity. This role sits at the intersection of organizational science, behavioral research, and people strategy – developing novel frameworks and conducting systematic research that drives evidence-based people decisions across our growing organization. This role offers the opportunity to make a significant impact on both our recruiting practices and the broader field of people science at a leading AI safety company.

Salary

USD 285,000 - 380,000

Requirements

Skills

  • Hold an advanced degree (Master’s or PhD) in I/O Psychology, Organizational Behavior, Statistics, Data Science, Economics, Behavioral Science, or a related research field
  • Have experience with selection research, assessment validation, psychometrics, or recruiting funnel analytics
  • Are comfortable working in the People Analytics tech stack and collaborating with data engineers
  • Are proficient in SQL and Python/R, with experience in statistical analysis and machine learning
  • Have experience with data visualization and can tell compelling stories with research findings
  • Possess excellent communication skills and can influence stakeholders at all levels
  • Thrive in ambiguity and can balance rigor with pragmatism
  • Have a track record of challenging assumptions with data and changing long-held practices
  • Can navigate sensitive topics diplomatically while maintaining analytical rigor
  • Demonstrate intellectual humility and comfort with iterative discovery
  • Use data to improve how organizations find, assess, and hire talent
  • Bachelor’s degree or an equivalent combination of education, training, and/or experience

Responsibilities

  • Design and execute systematic research studies to answer fundamental questions about recruiting funnel health, assessment quality, candidate experience, and quality of hire
  • Generate and test hypotheses about sourcing strategies, interview design, and selection decisions using rigorous experimental and quasi-experimental methods
  • Conduct mixed-method research to understand what are the drivers and blockers to recruiting operations
  • Navigate research ethics considerations when studying candidate data, ensuring responsible research practices
  • Design and execute validation studies to assess the quality of interviews and other selection tools
  • Utilize psychometric techniques to analyze and improve interviewer calibration and rating consistency
  • Lead investigative research into innovative approaches for candidate assessment
  • Design the metrics framework for recruiting org health — defining the canonical KPIs, dimensions, and definitions that leadership uses to understand funnel performance, capacity, and hiring quality
  • Establish the governance and definitional rigor that keeps metrics consistent across tools and reporting surfaces
  • Architect analytical solutions that convert research insights into actionable products, empowering stakeholders to execute data-driven scenario and strategic planning
  • Quantify the adoption and downstream impact of deployed tools, driving iterative improvements
  • Build compelling visualizations and dashboards that make complex research findings accessible to diverse audiences
  • Present research findings to senior leadership with clear, actionable recommendations

Technologies

SQLPythonRBigQuerymodern data stack toolsGreenhouseGemModernLoopnetwork analysismachine learningadvanced statistical methods

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