Data Scientist, AI for Biopharma – Hybrid Lyon

Sanofi Group; Lyon; Hybrid; EUR 54,000 - 73,000; Full time

Benefits offered by this job

Fixed salary + incentive

Health insurance

Remote work up to 2 days/week

Public transport coverage

Mobility opportunities

Job summary

Sanofi Group in Lyon is seeking a Data Scientist to advance digital transformation across Manufacturing & Supply. You will work with real-time IoT data, build AI/ML models, and deliver production-ready solutions in a hybrid role (60% office / 40% remote).

The ideal candidate has strong coding skills, experience deploying ML/DL in production, and a track record across data mining, forecasting, and visualization. Collaboration with engineers and scientists is essential.

Qualifications

• Experience delivering deployable AI/ML solutions in production.
• Hands-on data mining with large, diverse data sources.
• Experience working in healthcare/biopharma is a plus.

Responsibilities

• Collaborate with business teams to translate requirements into technical specs.
• Develop ML/AI models, experiments, and production-ready code.
• Industrialize AI/ML solutions with MLOps practices.
• Lead data analysis, visualization, and storytelling to inform decisions.
• Mentor junior data scientists and analysts.

Skills

Deployable code

Production-ready software

ML/DL approaches

Big data / data mining

IoT / time series forecasting

Healthcare domain experience

Cross-functional collaboration

Data visualization storytelling

CI/CD / orchestration

Python / R

Education

PhD in quantitative field or MSc with strong coding

Tools

Tableau

Power BI

Streamlit

Plotly

SQL / NoSQL / Graph / TimeSeries DBs

APIs

Job description

Sanofi Group in Lyon is seeking a Data Scientist to advance digital transformation across Manufacturing & Supply. You will work with real-time IoT data, build AI/ML models, and deliver production-ready solutions in a hybrid role (60% office / 40% remote).

The ideal candidate has strong coding skills, experience deploying ML/DL in production, and a track record across data mining, forecasting, and visualization. Collaboration with engineers and scientists is essential.