Quantitative Ux Researcher

OpenAI OpenAI · AI Frontier · San Francisco, CA · Data Science

This role focuses on quantitative user experience research to inform product decisions at OpenAI. The researcher will design and execute studies, analyze behavioral data, and translate findings into actionable recommendations. While the company develops AI, this role's core craft is UX research, not AI/ML model development.

What you'd actually do

  1. Design and execute quantitative research across the product lifecycle, from foundational understanding to concept validation, prototyping, and usability evaluation.
  2. Partner with product managers, designers, engineers, and data scientists to identify high-impact opportunities where quantitative insights can meaningfully shape product decisions.
  3. Lead rigorous, customized studies that answer both strategic and tactical questions, using methods such as surveys, experiments, and behavioral data analysis.
  4. Translate complex data into clear, actionable recommendations that drive alignment and decision-making across teams.
  5. Apply strong survey methodology and statistical rigor to ensure findings are valid, reliable, and decision-ready.

Skills

Required

  • 5+ years of experience working in user experience research, market research, data science, and/or a related field with a strong focus on quantitative methods.
  • Expertise in quantitative research, with proficiency in statistical analysis, experimental design, survey methodology, and behavioral data analysis.
  • Strong data analysis skills using tools such as SQL and Python.
  • Exceptional written and verbal communication skills, with the ability to influence decision-making at all levels.
  • Proven experience leading quantitative research projects that have made a lasting impact on product and design decisions.

Nice to have

  • Experience working with senior stakeholders.
  • A drive for excellence and the ability to consistently raise the bar.

What the JD emphasized

  • quantitative methods
  • quantitative research
  • quantitative research projects