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OpenAI is seeking a Product Data Scientist to drive product data science strategy and execution across youth, families, and learning audiences. This role owns the data science function for under-18 audiences, emerging opportunities for children under 13, family experiences, and education broadly.
You will shape product strategy by sizing unmet needs and growth opportunities, helping teams prioritize investments based on user value, reach, evidence, and effort. You'll develop audience-specific measurement frameworks spanning activation, task success, learning progress, satisfaction, and retention, connecting these metrics to product goals and assessing whether repeat use reflects meaningful benefit.
Key responsibilities include analyzing user journeys, funnels, and cohorts to uncover where people find value and what drives return visits. You'll combine behavioral data with surveys and user research to explain differences across ages, family roles, and learning contexts. You'll design experiments and holdouts to evaluate product and model changes, applying causal inference methods when randomization is impractical, and making assumptions explicit while accounting for seasonality and segment-specific effects.
You'll translate findings into product decisions by working with partners from hypothesis through launch and iteration, recommending what to build, change, expand, or stop with clear explanations of expected impact and uncertainty. You'll build reliable measurement infrastructure by partnering with engineering on instrumentation, dataset quality, and consistent audience definitions, creating reusable analyses and dashboards that enable teams to answer recurring questions independently.
The role requires creating alignment across multiple teams—Chat Product, Growth, Foundations, SafeSys, and others—bringing a coherent view of audience value to work spanning distributed ownership and incomplete evidence. You'll work closely with product managers, engineers, designers, and researchers, focusing on product value and growth while dedicated teams own policy and safety.
Requirements:
- Demonstrated record of influencing product strategy and improving user outcomes through hands-on data science, from ambiguous questions to decisions with measurable impact
- Strong SQL and Python skills with sound statistical judgment
- Practical experience with experiments, causal inference, cohort analysis, and measurement design
- Ability to develop useful definitions of product value, validate imperfect proxies, and distinguish short-term metric movement from lasting improvement
- Clear communication and strong product judgment; ability to make recommendations, explain limitations, and influence cross-functional collaborators without formal authority
- Comfort setting priorities independently across broad scope, staying close to users, and moving between strategic and detailed analytical work
- Helpful experience: consumer product growth, youth or family products, learning and education, generative AI, measuring learning outcomes, combining quantitative and qualitative research, or evaluating products whose value emerges over time
