- Design segmentation solutions using clustering techniques such as K-Means, GMM, or DBSCAN.
- Build customer-level features based on recency, frequency, monetary value, and lifecycle indicators.
- Utilize SHAP and other explainability techniques to interpret model behavior and create customer narratives.
- Contribute to targeting, campaign analytics, propensity modeling, and churn prediction.
- Define marketing KPIs and align analytical outputs with business objectives.
- Present findings to stakeholders through visualizations and business-focused language.
- Collaborate with Data Engineers and BI teams to write reproducible, well-documented code.
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