Descrizione
About the role In this role, you will act as the predictive engine for customer lifecycle management across multiple product lines. You will bridge advanced machine learning with tangible business outcomes—building, productionising, and monitoring predictive models that drive cross-sell conversion, retention strategies, and churn mitigation. This is a production-focused data science role where you will design scalable data pipelines in Databricks, deploy robust models, and collaborate directly with product, marketing, and retention teams to turn analytical insights into high-impact operational workflows.
Key responsibilities
Customer Analytics & Scoring Frameworks: Design, develop, and refine customer segmentation, propensity, future value, and risk-scoring frameworks across multi-product portfolios using structured transactional, behavioral, and intermediary data. Predictive & Churn Modeling: Build, evaluate, and refresh machine learning models (including classification, gradient boosting, and survival models) to proactively predict customer churn, lifetime value, and cross-sell opportunities. Feature Engineering & Pipeline Automation: Perform end-to-end feature engineering and construct automated ETL/ML data pipelines in cloud environments (Databricks) to operationalise model outputs at scale.
MLOps & Model Governance: Own model deployment, scheduling, orchestration, and continuous performance monitoring (handling data drift, feature decay, and model degradation in producti
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