À propos de Mohamed Yassine
Français
Bilingue ou natif
Anglais
Capacité professionnelle complète
Expériences
- KPITData & AI Engineer | Team Leadermars 2023 - mars 2026 (3 ans)○ Started, Led and mentored a team that grew from 3 to 8+ data engineers, owning delivery, architecture decisions, and technicalroadmap for data and AI solutions across multiple projects○ Designed and deployed an LLM-based test generation system using LangChain (RAG, toolcalling, MCP), generating structured test cases from specifications and engineering data○ Built end-to-end pipeline including retrieval (vector DB), prompt engineering, evaluation loops,and integration into CI workflows○ Developed APIs and CLI tools enabling seamless integration into existing engineering workflows○ Architected and implemented scalable data pipelines processing multi-source engineering dataacross 5+ projects and supporting tens of dashboards and BI reports, improving data availabilityand reliability for analytics○ Established best practices for code quality, CI/CD, and deployment, reducing production issuesand accelerating delivery cycles○ Collaborated with stakeholders to translate business needs into technical solutions for BI anddashboarding and driving adoption of AI-powered workflowsPython, LangChain, DBT, Airflow, MS SQL, Grafana, Power BI, OpenwebUI, Docker, CI/CD
- VamstarSenior Data EngineerSANTÉ & BIEN-ÊTREjanvier 2022 - juillet 2022 (6 mois)3303 N Mississippi Ave #500, Portland, OR 97227, USAWork on AI components of a health care data intelligence platform :- In a Health Care Tendering context, build Machine Learning/ Statistical Solutions for price recommendation and win likelihood prediction- Implement, test and publish the built solutions as APIs
- Openvalue / Société GénéraleMachine Learning EngineerBANQUE & ASSURANCESnovembre 2020 - décembre 2021 (1 an et 1 mois)94120 Fontenay-sous-Bois, FranceAs a Machine Learning Engineer in the team MOSAIC (More Security with Artificial Intelligence), contribute to the development of Anti-Fraud tools based on Machine Learning algorithms.- Building Big Data pipelines- Modelization of customers paiment habits- Training ML algorithms for frauds detection on features that measure the gap between the scored operation and the client habits- Developing a monitoring tool
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Formations
- Master of EngineeringEcole Centrale de Nantes2016Master of Engineering (M.Eng.), Engineering
- Master of ScienceUniversité Pierre et Marie Curie (Paris VI)2017Master of Science (MSc), Statistics & Data Science