End-to-End Demand Forecasting for Global Retail
Multi-scale demand forecasting and inventory optimization using deep learning—reduced stock-outs/overstocks, agile supply chain.
Supply Chain Impact
Advanced forecasting and optimization for retail supply chain
Project Details
Decathlon
Retail – Supply Chain Forecasting & R&D
2024–2025
Mission
Lead Senior Data Scientist – Forecast Supply Chain & R&D
Supply Chain Forecasting & Optimization
Long-term mission / Paris, France
Development of predictive models including RNN and LSTM networks to capture complex temporal dynamics of demand. Stock and replenishment optimization to reduce stockouts and overstocks. Industrialization: automation of pipelines, continuous integration, and model monitoring.
Contexte & Environnement
Decathlon, a leader in retail and e-commerce, faced major challenges in supply chain forecasting and inventory optimization. The complexity of multi-warehouse and multi-channel supply chains, combined with dynamic consumer behaviors and strong seasonality, required advanced predictive models.
1 Project Manager / 4 Data Scientists / 2 Data Analysts / 1 ML Engineer
Databricks on AWS S3 with Airflow orchestration
Objectifs Cles
Technologies & Infrastructure
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