À propos de Yannis
AI & Automation Engineer with experience in data science, DevOps, and software development. Contributed to major fraud detection systems and automation tools across teams. Passionate about building smart systems, from LLM apps to embedded hardware and 3D modeling.
Anglais
Bilingue ou natif
Français
Bilingue ou natif
Espagnol
Notions
Accepte de travailler sur site
Paris (jusqu’à 50 km)
Expériences
- Société GénéraleData Scientist / Engineer / MLOps / DevOpsBANQUE & ASSURANCESnovembre 2023 - Aujourd'hui (2 ans et 7 mois)Montreal, QC, Canada• Designed and deployed AI models (XGBoost, Gradient Boosting Machines) to detect and counter fraud, significantly reducing adversarial impact on existing systems.• Orchestrated workflows with Airflow for distributed ML processes.• Developed internal automation tools using LLMs, streamlining repetitive tasks and operational workflows.• Integrated NLP and semantic modeling for advanced fraud pattern recognition.• Built scalable data pipelines and conducted feature engineering within Linux-based environments.• Created interactive applications for process mapping and automation using Streamlit, React Flow, and Angular.• Engineered authentication systems and managed sensitive data with HashiCorp Vault.• Worked with PostgreSQL, public/private cloud platforms, and OpenAI's APIs for intelligent service integration.• Managed containerized environments and application scaling via Kubernetes, JFrog Artifactory, CI/CD.
- NibaData Science Consultantoctobre 2022 - août 2023 (10 mois)Paris, France• Developed an AI-powered Outlook draft assistant to automatically generate business emails, reducing redundancy and significantly improving employee productivity.• Built an internal chatbot to support coaching service teams by answering recurring operational questions and streamlining internal knowledge access.
- BNP Paribas CardifEngineering Apprenticeseptembre 2019 - août 2022 (2 ans et 11 mois)France• Developed a web application for actuarial business planning, enabling actuaries to generate accurate insurance forecasts, using Angular (TypeScript), .NET (C#), and Python APIs within an Agile framework.• Conducted advanced analytics on insurance claims using various machine learning techniques in Python and Jupyter, delivering data-driven insights.• Built a reusable Python package for actuarial provision calculation, improving efficiency and consistency.• Engineered data pipelines, ETL scripts, and automation tools to streamline data ingestion and enhance processing reliability.• Managed and maintained the Data Lab Domino Platform, a GPU-enabled, cloud-based Jupyter notebook environment to accelerate model development and analytics workflows
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Formations
- Engineering Master's Degree AIESIEA - École d'Ingénieur·e·s d'un numérique utile2022Engineering Master's Degree AI
- Baccalauréat SciencesLycée Les Pierres Vives2017Baccalauréat Sciences