Research Scientist, Intelligent Talent Acquisition

Amazon Amazon · Big Tech · Arlington, VA · Human Resources

Research Scientist role focused on applying advanced statistical techniques and machine learning to analyze large datasets for optimizing candidate evaluation processes and improving hiring excellence within Amazon's Talent Acquisition operations. The role involves designing large-scale personnel selection research, exploring emerging technologies, and translating complex findings into actionable strategies.

What you'd actually do

  1. Design large-scale personnel selection research that shapes Amazon’s global talent assessment practices across a variety of topics (e.g., assessment validation, measuring post-hire impact)
  2. Partner with key stakeholders to create innovative solutions that blend scientific rigor with real-world business impact while navigating complex legal and professional standards
  3. Apply advanced statistical techniques to analyze massive, diverse datasets to uncover insights that optimize our candidate evaluation processes and drive hiring excellence
  4. Explore emerging technologies and innovative methodologies to enhance talent measurement while maintaining Amazon's commitment to scientific integrity
  5. Translate complex research findings into compelling, actionable strategies that influence senior leader/business decisions and shape Amazon's talent acquisition roadmap

Skills

Required

  • PhD in a quantitative field, or MS degree and 1+ years of quantitative field research experience
  • Experience investigating the feasibility of applying scientific principles and concepts to business problems and products
  • Experience in applied selection research, job analysis, test development, and validation
  • Foundational skills in conducting experimental research studies and data analysis
  • Proficiency in scripting for data analysis (e.g., R, Python)

Nice to have

  • Experience influencing internal and external stakeholders
  • PhD in Industrial/Organizational Psychology or related field
  • Familiarity with using GenAI tools and Large Language Models (LLMs) in personnel selection research
  • Experience developing and maintaining global hiring assessments
  • Experience conducting experimental research in an industry environment
  • Excellent written and oral communication skills

What the JD emphasized

  • quantitative field research experience
  • applied selection research
  • test development
  • validation
  • experimental research studies
  • data analysis
  • scripting for data analysis
  • GenAI tools
  • Large Language Models (LLMs)
  • personnel selection research

Other signals

  • state-of-the-art research
  • advanced software tools
  • new AI systems
  • machine learning algorithms