Data Scientist, People Innovation
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 tha
What this role actually needs.
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 tha Responsibilities: - 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. - 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. Requirements: - 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. Company context: OpenAI builds frontier AI systems, research infrastructure, and applied products for developers, enterprises, and global users.
Day-to-day expectations
OpenAI lists these responsibilities for the Data Scientist, People Innovation role.
- 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.
- 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.
What a strong candidate brings
These requirements are extracted from the source listing and normalized for UpJobz readers.
- 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.
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Source: jobs.ashbyhq.com · Source ID: 82a30978-e4d9-4f64-aae2-b20877e052c0 · Confidence: 97/100 · Last checked: May 7, 2026
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