Within its global transformation, the Digital, Data & Tech (DD&T) department drives Lesaffre’s digital and data journey across four strategic pillars:
- Smart Operations (industrial efficiency & sustainability)
- Augmented R&D (accelerated innovation through data & AI)
- Customer Centricity (personalized and data-driven customer engagement)
- Empowered Enterprise (AI copilots and decision support)
As a Senior Data Scientist, you will be a key contributor to Lesaffre’s AI transformation, designing, developing, and deploying advanced AI models to solve complex business challenges across industrial, R&D, and commercial activities.
You will work within an agile squad alongside Product Managers, Data Engineers, and MLOps specialists to deliver reliable, scalable, and impactful AI solutions.
You will act as a technical expert, ensuring that models are built with quality, explainability, and measurable business value.
Your main missions will be :
1. Design and Delivery of AI Solutions
- Lead the end-to-end development of Data Science models, from scoping to production.
- Build predictive, prescriptive, and generative AI models to improve operational performance, quality, and decision-making.
- Collaborate closely with Product Managers, Data Engineers, and business experts to translate business needs into concrete solutions.
2. GenAI and Productivity Enhancement
- Use GenAI code assistant tools (e.g., GitHub Copilot, Claude, …) to accelerate coding, testing, and documentation.
- Contribute to agentic AI and copilot initiatives empowering Lesaffre employees through conversational interfaces.
- Promote responsible and efficient use of GenAI tools within the team.
3. Industrialization and MLOps
- Ensure robustness, reproducibility, and scalability through MLOps standards (MLflow, DVC, CI/CD, Docker).
- Work with Data Engineers to optimize data pipelines and model serving in AWS / Snowflake environments.
- Monitor model performance, detect drift, and ensure continuous improvement.
4. Governance and Ethics
- Apply Lesaffre’s AI Governance and Ethical AI Charter, ensuring fairness, transparency, and compliance with the EU AI Act.
- Document models, datasets, and assumptions to ensure auditability and responsible AI practices.
5. Knowledge Sharing and Community Contribution
- Share expertise and best practices with peers across the AI Community of Practice.
- Support upskilling initiatives and contribute to methodological and technical excellence.