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 SMB customers through agentic lifecycle and sales experiences Adapt messaging, creative, and outreach using real-time behavioral signals Power intelligent routing, targeting, and engagement decisions at scale, with minimal human-in-the-loop In this role, you'll be embedded with Product and Engineering to ensure these systems drive measurable business outcomes.

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.
• Familiarity with large language models and AI-assisted operations platforms
• Experience working on operational automation and decision systems (routing, prioritization, optimization)
• Experience operating in early-stage or rapidly evolving environments, including building measurement and experimentation frameworks from scratch.
• About OpenAI
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