Data Sciences Intern - January 2027 - Paris

Description du poste

Want to join the world's No. 2 in wines & spirits and work among convivial teams? Pernod Ricard is looking for Data & AI Intern for 6 months from January to June 2027. You will be based at the Island, our office in central Paris (Saint Lazare Train Station, Paris 8).

You will participate in the technical implementation of one of the key data science programs in the Group's transformation plan, in the development of the project's code base, and in the maintenance of existing Machine Learning and optimization models in the “Data & AI” team. The team also builds the Generative AI and agentic components of our digital products, and the engineering practices that keep them reliable in production.

Your key missions

• You will contribute to the development of the program's algorithmic building blocks, from classical Machine Learning and optimization models to Generative AI components (LLM based pipelines, retrieval augmented generation, agentic workflows).
• You will be responsible for the maintenance and re-training of existing models, including monitoring of data drift, performance, latency and cost in production (MLOps and LLMOps practices).
• You will evangelize data science and AI concepts to deployment managers.
• You will help design and run the evaluation of AI systems: building benchmarks, measuring quality and robustness, and documenting failure modes before deployment.
• You will contribute to the responsible AI frame of the program: traceability of data and prompts, model and system documentation, and alignment with the Group's AI policy and applicable AI regulation.

If you recognize yourself in the description below, don’t wait to apply!

• You master the Python language and object-oriented programming, a theoretical grounding in the field of Data Science and Machine Learning, as well as knowledge of data management concepts (ETL, API, data storage solutions, SQL, etc.). Knowledge of versioning tools (GitHub) is a plus. Exposure to Deep Learni

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