Job Description

Who we are ?

Pierre Fabre is the 2nd largest dermo-cosmetics laboratory in the world, the 2nd largest private French pharmaceutical group and the market leader in France for products sold over the counter in pharmacies.

Its portfolio includes several medical franchises and international brands including Pierre Fabre Oncologie, Pierre Fabre Dermatologie, Eau Thermale Avène, Klorane, Ducray, René Furterer, A-Derma, Naturactive, Pierre Fabre Oral Care.

Established in the Occitanie region since its creation, and manufacturing over 95% of its products in France, the Group employs some 10,000 people worldwide. Its products are distributed in about 130 countries. 86% of the Pierre Fabre Group is held by the Pierre Fabre Foundation, a government-recognized public-interest foundation, while a smaller share is owned by its employees via an employee stock ownership plan.

In 2019, Ecocert Environment assessed the Group’s corporate social and environmental responsibility approach in accordance with the ISO 26000 sustainable development standard and awarded it the “Excellence” level.

Pierre Fabre is recognized as one of the "World's Best Employers 2021" by Forbes. Our group is ranked in the Top 3 in the cosmetics industry and in the Top 10 in the pharmaceutical industry worldwide.

Your mission

We are seeking in Toulouse (Oncopole- Langlade location) a talented and highly motivated Senior Data Scientist - Competitive Intelligence & Clinical Operations with strong expertise in Large Language Models (LLMs), NLP, and agentic AI systems to build Pierre Fabre’s in silico Competitive Intelligence (CI) capabilities and scale advanced analytics for Clinical Operations (ClinOps).

As a key member of the Data Science & Biometry Department within Pierre Fabre R&D Medical Care, you will work closely with the Competitive Intelligence team to design and implement the computational foundations of CI. The architectural choices you make will define our CI capabilities for years to come.

You will also contribute to clinical development in oncology and rare diseases, operating at the interface with Clinical Operations.

The role sits within the Methods & Innovation team, responsible for cross-functional AI initiatives and advanced methodological development.

Your role within a pioneering company in full expansion:

Key Responsibilities

• Partner with stakeholders to translate strategic and scientific questions into operational AI solutions.
• Design and deploy advanced analytics solutions for competitive intelligence landscape analyses.
• Build scalable CI tools to support strategic decision-making across drug discovery and clinical development programs.
• Optimize the identification, characterization, and prioritization of investigational sites using heterogeneous internal and external data sources.

• Design, develop, and deploy LLM-based agents for automated data collection, analysis, and synthesis.
• Implement advanced NLP solutions (information extraction, classification, entity recognition, and document-level or cross-source summarization).
• Build and maintain Retrieval-Augmented Generation (RAG) architectures leveraging vector databases and structured knowledge sources.
• Contribute to agentic data pipelines for collection, normalization, fusion, and continuous enrichment.

• Operate in cloud-based environments, integrating APIs, pipelines, and scalable compute resources.

This position is compatible with teleworking up to 2 days a week according to company rules.

We offer an attractive remuneration/benefits package: Incentives, profit-sharing, Pierre Fabre shareholding with matching contribution, health and provident insurance, 16 days of holidays (RTT) in addition to 25 days of personal holidays, public transport participation.

Who you are ?

Your skills at the service of innovative projects:

Education

• Master’s degree or PhD in Data Science, Artificial Intelligence, Statistics, Computer Science, or a related field.

Experience

• 4–5 years of experience in applied Data Science.
• Strong hands-on experience with NLP and LLM-based systems, including agentic or autonomous workflows.
• Experience working in cloud environments.
• Prior exposure to pharma, biotech, or life sciences is required.

Technical Skills

• Python proficiency and experience with machine learning frameworks (e.g., scikit-learn, PyTorch).
• Strong knowledge of the NLP / LLM stack, including embeddings, fine-tuning, RAG architectures, and vector databases.
• Solid data engineering fundamentals (APIs, web scraping, data pipelines, data modeling).
• Ability to produce clear visualizations and insights for non-technical stakeholders.

Soft Skills & Mindset

• Strong analytical and structured thinking.
• Ability to translate scientific, operational, and strategic needs into effective AI-driven solutions.
• Excellent cross-functional collaboration skills.
• High intellectual curiosity and innovation mindset.
• Professional proficiency in English (written and oral).

We are convinced that diversity is a source of fulfillment, social balance and complementarity for our employees, which is why our offers are open to all, without restriction.