Sr. Staff Quantitative Product Researcher

Job Description

Responsibilities

• Lead the development of user-centered metrics end-to-end: define the construct, design and validate the survey instrument, establish reliability and sensitivity, guide the experimentation plan to prove the metric can move, and partner with DS and Eng to build behavioral proxies or predictive models when appropriate
• Extend measurement work into model stewardship — inform retraining decisions, evaluate generalizability across user segments, and stress-test where models do and don’t hold up
• Conduct deep-dive learning analyses to uncover the drivers and levers behind key metrics, and translate those into actionable direction for product and DS partners
• Set and execute the learning agenda across a broad problem space — prioritize the questions that matter most, choose the right methods (surveys, behavioral analysis, quasi-experimental approaches, modeling), and work on the right project at the right time
• Show up as an equal partner to Data Science and Engineering, shaping the direction of measurement work rather than executing against someone else’s spec
• Synthesize across behavioral analyses, experiment results, qualitative insights, and your own work to inform product and business decisions
• Present to senior leadership and tailor socialization for those audiences
• Partner with research managers to set quantitative research direction and mentor more junior quantitative researchers

What we’re looking for:

• 7+ years of quantitative user research experience with large-scale consumer data, including a track record of leading metric development end-to-end — from construct definition through survey validation, experimental validation, and behavioral proxy/predictive modeling
• Deep expertise in survey methodology (construct validity, reliability, sensitivity), statistical modeling, experimentation at scale, and behavioral analysis
• Experience informing ML model evaluation and maintenance — retraining triggers, generalizability across segments, and known failure modes
• Fluency in R or Python and SQL, and strong data visualization skills
• Demonstrated ability to operate as a peer to Data Science and Engineering — guiding the direction of technical work, not just contributing to it
• Proactive — identifies the important questions and problems even when stakeholders aren’t asking, and brings partners along
• Experience working horizontally across teams, developing strategy with xfn partners, and presenting to senior leadership
• Experience successfully leveraging AI tools in the research process with proper discernment and a high quality bar
• PhD preferred in a computational social science (economics, sociology, psychology), statistics, computer science, or related field — or equivalent practical experience

Are you interested in this position?
Apply by clicking on the “Apply Now” button below!
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