About 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.
English
Native or bilingual
French
Native or bilingual
Spanish
Basic
Can work on-site
Paris (up to 50km)
Experience
- Société GénéraleData Scientist / Engineer / MLOps / DevOpsBANKING AND INSURANCENovember 2023 - Today (2 years and 7 months)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 ConsultantOctober 2022 - August 2023 (10 months)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 ApprenticeSeptember 2019 - August 2022 (2 years and 11 months)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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Education
- Engineering Master's Degree AIESIEA - École d'Ingénieur·e·s d'un numérique utile2022Engineering Master's Degree AI
- Baccalauréat SciencesLycée Les Pierres Vives2017Baccalauréat Sciences