Forward Deployed Marketing Data Scientist

Contenido del rol extraído en secciones para revisar más rápido.

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.

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.

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.

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.

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.

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.