# Data Scientist at Sanofi

Sanofi is hiring a Data Scientist in Lyon, France. It pays €57k a year and Level rates it Little AI ●○○○; you can [apply on Sanofi](https://jobsbylevel.com/go/c89fa670-182f-49d9-a490-a06a031eb567?utm_medium=ai-agent).

AI Level 1, AI centrality 12 out of 100. Lyon.

## Details

- Company: [Sanofi](https://jobsbylevel.com/companies/sanofi)
- AI level: AI Level 1 (score 12 out of 100)
- Location: Lyon
- Salary: €57k
- Posted: November 5, 2026
- Apply: https://jobsbylevel.com/go/c89fa670-182f-49d9-a490-a06a031eb567?utm_medium=ai-agent
- Free CV review for this job: https://jobsbylevel.com/cv-review?job=data-scientist-at-sanofi-db538b

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## Description

Le contenu du poste est libellé en anglais car il nécessite de nombreuses interactions avec nos filiales à l’international, l’anglais étant la langue de travail. Job title : Data Scientist Location: Lyon, M&S Accelerator Work Arrangement: Hybrid (Three days from office and two days from home) About the job As a Data Scientist within our Digital Manufacturing & Supply (M&S) Accelerator , you'll take ownership of turning real-time signals from our factories and labs into decisions that matter — working at the intersection of drug development, advanced manufacturing, and cutting-edge AI. Ready to get started? Join Sanofi's Manufacturing & Supply team right in the heart of Lyon, in a vibrant startup-style environment in the city centre. You'll support 12 blockbuster launch teams and 40 global factories across R&D and M&S, helping accelerate the launch of new medicines, build digitalised "Lighthouse" factories, and drive manufacturing performance improvements — all while enjoying an easy commute and a great work-life balance in one of France's most dynamic cities. About Sanofi: We're an R&D-driven, AI-powered biopharma company committed to improving people's lives and delivering compelling growth. Our deep understanding of the immune system – and innovative pipeline – enables us to invent medicines and vaccines that treat and protect millions of people around the world. Together, we chase the miracles of science to improve people's lives. Main responsibilities Partner with business teams to understand requirements and translate them into technical solutions, working with a good degree of autonomy Own the ingestion, cleaning, and harmonisation of IoT and sensor data from a mixed estate — some fully connected and streaming, plenty of it legacy, manual, or messy. A meaningful part of the role is data cleaning and wrangling: it's the foundation everything is built on, and doing it well is genuinely high-impact here Design and deliver time-series models — forecasting, anomaly detection, and monitoring — on streaming sensor data to drive manufacturing performance and quality Design, build, and support real-time and streaming data pipelines together with engineers and MLOps, and help bring legacy sites up to a usable state Write highly optimised, production-ready code, taking models from experiment through to deployment Scope, define, and deliver AI-based data products end to end, using data analysis, visualisation, and storytelling Be accountable for the robustness of the AI solutions you deliver, applying responsible AI practices (monitoring, explainability, trustworthiness, ethics) Contribute to — and help raise the bar within — the global data science community of practice Support junior data scientists and analysts with informal guidance and code review You'll also work across the wider AI portfolio — including LLMs, Retrieval-Augmented Generation (RAG), and agentic AI workflows — as our products increasingly blend sensor intelligence with GenAI. Strong here is a plus, but IoT and time-series is the core of this role. About you You're a capable data scientist with a few years under your belt, genuinely excited by physical-world data — sensors, signals, and the machines that produce them. You can take a problem from vague business need to deployed model with limited hand-holding, and you've got a keen eye for improvement opportunities. Experience: Hands-on track record working with IoT data, sensor streams, or time-series (this is what we care about most) Demonstrated experience applying machine learning to real problems, ideally involving signals or temporal data Experience developing deployable code and taking models to production in an agile environment You're not put off by messy, real-world data — a big part of this role is turning inconsistent legacy data into something usable, and doing it well is where a lot of the value sits Knowledge of the pharmaceutical or chemical domain is a huge advantage — understanding of

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