About Jason
- Automation of time-consuming tasks: PDF extraction, Excel formatting, data integration from sensors or SQL databases.
- Business-oriented AI models: classification, prediction, time series, deep learning, based on your real use cases.
- Visualization & KPI monitoring: dynamic dashboards (Power BI, Looker, Streamlit) for quick decision-making.
- Custom AI Assistants: intelligent chatbots capable of directly answering your questions from your own documents (NLP, LLM, RAG, Embeddings).
French
Native or bilingual
English
Fluent
Experience
- 4CAD GroupAI ArchitectJanuary 2026 - Today (7 months)Definition of the group's LLM strategy and management of the data team.🎯 Objective: position 4cad Group as a sovereign player in its data by arbitrating between On-Premise solutions and Cloud APIs.➡️ Comparative benchmarks of LLMs (On-Premise vs Cloud) to evaluate performance, cost, and GDPR compliance — delivery of a strategic arbitration report to the COMEX.➡️ Architecture of clustering solutions for the automotive sector, aimed at optimizing industrial production flows.➡️ Technical supervision and mentorship of a Data Scientist and an intern: code reviews, sprint planning, skill development.
- Schmidt GroupeFreelance Data ScientistSeptember 2025 - December 2025 (3 months)End-of-month commercial landing prediction model for sales management.🎯 Objective: enable sales teams to anticipate performance gaps mid-month and adjust actions in real-time.➡️ Development of a Time Series model using XGBoost, trained on sales history to accurately predict monthly landing.➡️ Design of custom Scikit-Learn pipelines with custom transformers to industrialize and ensure the reliability of preprocessing.➡️ Delivery of a production-ready solution, directly usable by teams without technical intervention.
- UniversitéData Scientist & AI Mentoring: RAG Chatbot for Biomedical ResearchMEDICALJune 2025 - July 2025 (1 month)Nantes, France➡️ Mentoring a PhD student in designing an intelligent chatbot capable of extracting and retrieving scientific information from research documents.➡️ Implementation of a RAG (Retrieval-Augmented Generation) architecture: document vectorization, FAISS index database, LLM integration via Langchain.➡️ Methodological framework, code review, and weekly technical support (Python, NLP, embeddings, Flask).🎯 Objective: facilitate access to medical knowledge within the scope of a biomedical sciences thesis.
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Education
- Machine Learning EngineerOpenClassroom2021Ingénieur Machine Learning
- Structural EngineerUniversité Laval2015Ingénieur
Certifications
- Google AnalyticsLa fusée2022
- Responsible DigitalManagExam2025