Forward Deployed Data Scientist

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

Own diagnostics, insights, and tuning for AI Decisioning campaigns Explain AI Decisioning's impact using counterfactuals, incrementality, and cohort analysis Debug performance issues, iterate on reward functions, and ensure agent recommendations align with customer goals Investigate experiment setups and surface actionable recommendations Work deeply with data in notebooks and customer warehouses Pull historical data for exploratory analyses using Polars/Pandas Modify and improve customer feature matrices for deep personalization Conduct SQL analyses in customer warehouses Build lightweight tooling for scale (templates, notebooks, scripts) Identify systemic gaps and influence ML reporting/introspection Communicate ML concepts clearly to non-technical stakeholders Present model insights and recommendations Explain decision engine concepts (cold start, transfer learning, exploration vs. exploitation) Partner with Solutions Consultants to identify and drive new opportunities