Machine Learning Engineer - PRISM - Supply Chain (f/m/d)

About Decathlon Decathlon aims to become the best sports digital platform and open ecosystem in the world. We want to enable customers to experience Decathlon through many local sport-centric experiences by connecting many third-party actors and services, in a secure and performant way. Our digital teams in Lille, Paris, and Amsterdam (and more…) which bring together more than 5000 collaborators are united to build and scale digital products with the aim to always deliver the best value to our users. With a presence in more than 70 countries, Decathlon is committed to innovation, sustainability, and customer satisfaction. Job Description Decathlon is seeking a talented Senior Machine Learning Engineer (MLE) to join our Demand and Assortment Planning department within the Supply Chain division. As an MLE at Decathlon, you will play a critical role in the industrialization, deployment, and monitoring of AI models. You will collaborate closely with Data Scientists, Data Engineers and Digital Product Managers to design and implement cutting-edge AI solutions that optimize our supply chain operations. Responsibilities Develop and implement AI models for demand and assortment planning in the supply chain domain. Collaborate with Data Scientists and Digital Product Managers to translate business requirements into scalable machine learning solutions. Collaborate with data engineering teams to optimize data pipelines and ensure timely availability of clean and relevant data for model training and inference. Implement strategies for model retraining and updating to adapt to changing market dynamics and business requirements. Industrialize machine learning models and deploy them into production environments. Monitor model performance and implement improvements to ensure accuracy and reliability. Work closely with cross-functional teams to integrate machine learning capabilities into existing systems and processes. Document best practices, standard operating procedures (SOPs),