Responsibilities1. Customer Analytics & CRMBuild and deploy segmentation models (RFM/RFMT, CLV, engagement tiers) for omni-channel retention (dine-in, app, delivery).Design and maintain churn prediction, uplift modeling, and win-back triggers, tracking incremental lift.2. Personalization & RecommendationRecommend voucher types, products, and timing via contextual bandits, hybrid recommenders, and rule-based systems.Ensure ROI and budget alignment for marketing incentives.3. Forecasting & OperationsForecast traffic, sales, and ingredient demand at daily/weekly/monthly levels using ARIMA, Prophet, GBDT, or deep learning models.Optimize staff scheduling (shift assignment) under constraints such as skills, peak hours, and labor rules.4. Experimentation & Causal InferenceDesign and analyze A/B tests, Difference-in-Differences, and causal ML models (DML, DR-Learner) to evaluate campaign or pricing impact.5. MLOps & DeliveryDeploy models to production (batch/API), manage feature stores, MLflow tracking, and monitor model drift/decay.Collaborate with Data Engineering and Product teams to ensure reliable data pipelines and mart/feature tables.6. Communication & Business PartneringTranslate business problems into ML approaches, articulate trade-offs between accuracy and speed, and communicate insights clearly to non-technical teams.