About the role
About
the Role We’re hiring a Data Scientist to support People Innovation Labs, a fast-moving engineering team embedded in the People organization focused on rethinking how we find and retain the best talent and empower everyone to do their best work. From recruiting to culture, we’re designing systems and products that give our People Team a significant edge by infusing OpenAI’s models and first-principles thinking into every aspect of our work. Our projects range from greenfield 0-1 products like OpenHouse (our internal knowledge hub) to AI-powered automations and scalable recruiting tools. We’re defining the future of work at OpenAI, creating a blueprint for how AI can supercharge productivity, culture, and innovation. In this role, you’ll be embedded with Product and Engineering to ensure our work drives measurable business outcomes. What You’ll Do Define success metrics for agentic recruiting and HR systems, including leading indicators that enable weekly iteration. Design measurement and experimentation frameworks for always-on systems across every stage of the candidate and employee lifecycle — using holdouts, staged rollouts, and quasi-experimental methods when needed. Partner with PMs and engineers to instrument, evaluate, and monitor launches so every meaningful release has observability and a credible read on incremental value. Translate behavioral and model-driven signals into decisions: what to scale, where to intervene, and how to allocate human and compute attention across segments. Build repeatable decision loops (pre-launch criteria → post-launch read → next action) that convert analysis into shipped changes. What We’re Looking For 10+ years in a quantitative role (e.g., Data Science, Decision Science), ideally at a product-led company or in the internal people software space. Deep grounding in experimentation, causal inference, and applied statistics, with experience designing and interpreting tests in real-world, always-on environments. Strong technical fluency in SQL and Python, including working directly with messy, incomplete behavioral data to quantify impact. Proven track record of translating results into shipped decisions (product, lifecycle, targeting, routing). Strong business judgment and a bias toward action: able to scope ambiguous problems, define success, and move quickly from insight to strategy. Excellent communicator and partner to PMs/Engineers; comfortable influencing stakeholders and presenting recommendations to senior leadership. Interest in building company culture and/or recruiting the world’s most talented people.
Amazon