Data Scientist

1. Customer, Growth & Commerce Intelligence

• Search, ranking, recommendations, and personalization
• Customer profiling, segmentation, lifetime value (LTV), churn analysis, and loyalty programs
• Optimization of acquisition, engagement, retention, and customer lifecycle
• Evaluation of marketing effectiveness, attribution, uplift, and experimentation

2. Monetization, Pricing & Promotions

• Dynamic pricing strategies and markdown optimization
• Assessment of promotion effectiveness and personalization of offers
• Ad relevance, bidding intelligence, and performance measurement
• Optimization of margins and revenue intelligence

3. Supply Chain, Planning & Availability

• Large-scale demand planning and forecasting
• Inventory management, replenishment, and allocation optimization
• Network planning, sales & operations planning (S&OP), and fulfillment intelligence
• Optimization of product availability, selection depth, and service levels

4. Store, Operations & Physical Retail Intelligence

• Enhancing store efficiency, labor optimization, and compliance monitoring
• Planogram analytics and assortment effectiveness
• Intelligence derived from computer vision, video, and sensor data
• Prevention of shrinkage, fraud, and loss

5. Platform, Automation & Next-Generation AI

• Embedding intelligent decision engines into workflows
• Agentic systems for automated planning, execution, and monitoring
• Modeling based on causal inference, simulations, and digital twins
• Reusable machine learning platforms, feature stores, and inference systems

Must-have skills

Retail recommendations

Good-to-have skills

PyTorch, TensorFlow, XGBoost