Qui sommes-nous ? Pierre Fabre est le 2ème laboratoire dermo-cosmétique mondial, le 2ème groupe pharmaceutique privé français et le leader des produits vendus hors prescription dans les pharmacies en France. Son portefeuille compte plusieurs franchises médicales et marques internationales dont Pierre Fabre Oncologie, Pierre Fabre Dermatologie, Eau Thermale Avène, Klorane, Ducray, René Furterer, A-Derma, Naturactive et Pierre Fabre Oral Care. Implanté depuis toujours en région Occitanie, fabricant plus de 95% de ses produits en France, le groupe emploie près de 10 000 collaborateurs dans le monde et distribue ses produits dans quelque 130 pays. Pierre Fabre est détenu à 86% par la Fondation Pierre Fabre, une fondation reconnue dutilité publique, et secondairement par ses collaborateurs à travers un plan dactionnariat salarié. En 2021, Ecocert Environnement a évalué la démarche de responsabilité sociétale et environnementale du Groupe selon la norme ISO 26000 du développement durable et lui a attribué le niveau Excellence . Pierre Fabre est reconnu comme lun des Meilleurs Employeurs du Monde 2021 par Forbes. Notre groupe est classé dans le Top 6 de lindustrie cosmétique et dans le Top 7 de lindustrie pharmaceutique dans le monde. Nous sommes convaincus que notre engagement et notre passion font préserver notre indépendance et vivre notre raison d'être. Votre 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 Fabres 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. Qui êtes-vous ? Your skills at the service of innovative projects: Education * Masters degree or PhD in Data Science, Artificial Intelligence, Statistics, Computer Science, or a related field. Experience * 45 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 collabor...