Forward Deployed Marketing Data Scientist

Responsibilities

• Own diagnostics, insights, and tuning for AI Decisioning campaigns

  • Explain why AI Decisioning is driving lift using counterfactuals, incrementality breakdowns, and cohort analysis.
  • Debug performance issues, iterate on reward functions, and ensure the agent’s recommendations align with customer goals.
  • Investigate experiment setups (send volumes, reachability, channel constraints) and surface actionable recommendations.

• Work deeply with data in notebooks and customer warehouses

  • Pull down historical data to run exploratory analyses using Polars / Pandas in Jupyter notebooks
  • Modify and improve customer feature matrices to unlock deep personalization.
  • Conduct deeper warehouse-level SQL analyses when insights aren’t available in the UI.

• Build lightweight tooling that enables scale

  • Create templates, notebooks, scripts, and repeatable workflows that improve how we analyze performance across customers.
  • Identify systemic gaps and influence the direction of ML reporting and introspection.

• Communicate ML concepts clearly to non-technical stakeholders

  • Present model insights and recommendations to marketers, analysts, and executives.
  • Explain how the decision engine handles cold start, message transfer learning, exploration vs. exploitation, and more.
  • Partner closely with Solutions Consultants to identify and drive new opportunities for uplift.

Requirements

• Strong ability to perform deep exploratory data analysis in Python (Polars / Pandas, Jupyter notebooks).
• Ability to write and interpret SQL for customer warehouse analysis.
• High-level understanding of ML modeling concepts (features, hyperparameters, reward functions, training windows).
• Excellent communication skills; able to explain technical reasoning simply and confidently to marketers.
• A customer-first attitude with high ownership and urgency when resolving issues.

Nice-to-Haves

• Experience setting up and analyzing marketing experiments such as A/B, multivariate tests.
• Prior experience in an applied ML, data science, analytics engineering, or forward-deployed role.
• Experience building lightweight internal tools or scripting solutions.

Compensation

Salary range: $140,000 - $220,000 USD per year (location independent, remote-first).