Data Scientist, Marketing Innovation

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.

What You’ll Do

• 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.
  

• 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.
  

Nice to have

• 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.