Product Data Scientist - Youth, Families and Learning

About the role We’re looking for a product data scientist to help OpenAI create more value and drive sustainable growth for young people, families, and learners. You’ll drive product data science across under-18 audiences, emerging opportunities for children under 13, family experiences, and learning and education more broadly. You’ll help decide where we should invest, what we should build, and how we’ll know it is working. This means understanding distinct audience needs, identifying promising use cases, and turning evidence into a clear product strategy. Your work will connect discovery and early product development with adoption, retention, and sustained user value. You’ll partner across Chat Product, Growth, Foundations, SafeSys, and other teams, working closely with product managers, engineers, designers, and researchers. The role focuses and owns product value and growth while dedicated teams own policy and safety. In this role, you will: - Shape strategy and prioritize opportunities. Size unmet needs and growth opportunities across audiences, use cases, and product experiences. Help teams choose where to invest and sequence work based on expected user value, reach, evidence, and effort. - Define what value and success mean. Develop an audience-specific measurement framework spanning activation, task success, learning progress, satisfaction, and durable retention. Connect these measures to product goals and assess whether repeat use reflects meaningful benefit. - Understand users and growth drivers. Analyze journeys, funnels, and cohorts to uncover where people find value, where they struggle, and what helps them return. Combine behavioral data with surveys and user research to explain differences across ages, family roles, and learning contexts. - Measure what changes actually cause. Design experiments and holdouts to evaluate product and model changes. Apply causal methods when randomization is impractical, make assumptions explicit, and account for seasonality, audience composition, and effects that differ across segments. - Turn findings into product decisions. Work with partners from initial hypotheses through launch and iteration. Recommend what to build, change, expand, or stop, explaining expected impact, uncertainty, and tradeoffs. Follow through to determine whether decisions delivered the intended results. - Build reliable measurement. Partner with engineering on instrumentation, dataset quality, and consistent audience definitions. Create reusable analyses and dashboards that make progress visible and let teams answer recurring questions independently. - Create alignment across teams. Bring a coherent view of audience value to work spanning multiple roadmaps. Help partners agree on priorities, success criteria, and the next questions to resolve, even when ownership is distributed and evidence is incomplete. You might thrive in this role if you have: - A record of influencing product strategy and improving user outcomes through hands-on data science, including work from an ambiguous question to a decision and measurable impact. - Strong SQL and Python skills, sound statistical judgment, and practical experience with experiments, causal inference, cohort analysis, and measurement design. - The 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. You can make a recommendation, explain its limits, and influence collaborators across functions without relying on formal authority. - Comfort setting priorities independently across a broad scope, staying close to users, and moving between strategic questions and detailed analytical work. Helpful experience Experience with consumer product growth, youth or family products, learning and education, or generative AI would be valuable. We also welcome experience measuring learning outcomes, combining quantitative and qualitative research, or evaluating products whose value emerges over time. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties re