Data Scientist, Marketing Innovation
About the Role We’re hiring a Data Scientist to support our Marketing Innovation pod, a cross-functional team building the internal tools and agentic systems that fundamentally change how we do marketing and serve customers. We build product-like systems that: Deliver high-touch, consultative experiences to millions of
What this role actually needs.
About the Role We’re hiring a Data Scientist to support our Marketing Innovation pod, a cross-functional team building the internal tools and agentic systems that fundamentally change how we do marketing and serve customers. We build product-like systems that: Deliver high-touch, consultative experiences to millions of Responsibilities: - Define success metrics for agentic marketing systems (e.g., incremental pipeline generated, conversion lift, rep hours saved), including leading indicators that enable weekly iteration. - Design measurement and experimentation frameworks for always-on systems across lifecycle automation, creative generation, targeting, and routing — 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. Requirements: - 10+ years in a quantitative role (e.g., Data Science, Decision Science), ideally at a product-led company supporting B2B growth, with exposure to SMB or scaled self-serve motions. - 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, Marketing Innovation role.
- Define success metrics for agentic marketing systems (e.g., incremental pipeline generated, conversion lift, rep hours saved), including leading indicators that enable weekly iteration.
- Design measurement and experimentation frameworks for always-on systems across lifecycle automation, creative generation, targeting, and routing — 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 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 supporting B2B growth, with exposure to SMB or scaled self-serve motions.
- 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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Data Scientist, Marketing Innovation is framed against UpJobz source checks, country scope, compensation visibility, and work-authorization signals so candidates can make a faster go/no-go decision.
United States tech market
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Compensation read
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Location read
Hybrid roles in San Francisco should be compared against commute, local salary bands, and nearby employer demand.
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Source: jobs.ashbyhq.com · Source ID: 7f299784-2c75-4d73-99e5-1e5043ec7b48 · Confidence: 97/100 · Last checked: May 7, 2026
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