Data Scientist

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 manufacturing processes, GxP, or lab environments will set you apart

Soft skills:

• Excellent written and verbal communication skills

• Experience working with multiple teams to drive alignment and results

• Service-oriented, flexible, positive team player

• Self-motivated, takes initiative

• Problem solving & critical thinking

Technical skills:

• Strong Python, and comfortable with at least one database system — time-series databases (e.g. InfluxDB, TimescaleDB) especially valued

• Solid command of time-series methods — forecasting, anomaly detection, signal processing — on streaming data

• Working knowledge of streaming / real-time data technologies (e.g. Kafka, Spark Streaming, MQTT or similar)

• Strong ML foundations: supervised/unsupervised learning, deep learning, with a solid grasp of the underlying theory

• Comfortable working in cloud and high-performance computing environments (AWS, GCP, Databricks, Apache Spark)

• Good software engineering practices — version control, testing, CI/CD, orchestration

• Experience with data visualisation tools (Power BI, Tableau, Streamlit, Plotly, seaborn, or similar)

• Experience handling sensitive data in critical environments (healthcare, etc.)

• Familiarity with LLMs, RAG, or agentic workflows is a plus, not a requirement

Education:

• Master's degree (or PhD) in engineering, computer science, mathematics, physics, statistics, or a related quantitative discipline with strong coding skills — backgrounds in chemical/process engineering, control systems, or signal processing are especially welcome

Languages:

• English and French

What we offer you: 

A fixed salary over 12 months, supplemented by a short-term incentive, as well as a collective variable compensation based on Sanofi Group results. 

Because taking care of our employees is also our mission:  

• Benefits & Well-being: Quality health insurance, extended maternity/parental leave (18/14 weeks), enhanced support in case of illness, teleconsultation and second medical opinion covered by Sanofi, as well as many other wellness programs to discover here. 

• Work-Life Balance: 31 days of paid leave + RTT depending on your status, remote work up to 2 days/week 

• Transportation: Public transport coverage up to 80% 

• Savings & Retirement: Group Savings Plan and PERCOL with employer matching, and PERO 

• Professional Development: Internal and international mobility opportunities, learning & development opportunities 

• And more: platforms dedicated to peer-to-peer recognition & service exchanges between Sanofi employees (carpooling, home exchanges, etc.), numerous CSE benefits... 

Why choose us?

We provide a highly open and collaborative environment, with the chance to work with a world-class team. You will be able to:

• Learn what it takes to build a service with a truly global reach

• Be part of an organisation that values diversity, inclusion, and the richness of different backgrounds and experiences

• Engage in meaningful work that combines the challenges of pharma, manufacturing, environmental matters, and technical fields — with abundant opportunities for professional growth and impact

• Grow your career at a company that's not only a leader in healthcare but a pioneer in digital transformation, shaping the future of global health

#LI-FRA #LI-Hybrid

Pursue progress, discover extraordinary

Better is out there. Better medications, better outcomes, better science. But progress doesn’t happen without people – people from different backgrounds, in different locations, doing different roles, all united by one thing: a desire to make miracles happen. So, let’s be those people.

At Sanofi, we provide equal opportunities to all regardless of race, colour, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, ability or gender identity.

Watch our ALL IN video and check out our Diversity Equity and Inclusion actions at sanofi.com!

The salary range for this position is :€48,000.00 - €64,000

Final compensation will be determined based on demonstrated experience, skills, location, and other relevant factors. Employees may be eligible to participate in Company employee benefit programs.