About Raphaël
- Build LLM-powered agentic systems to automate complex workflows and accelerate business outcomes.
- Deploy production-ready machine learning models for prediction, optimization, and intelligent decision-making.
- Engineer scalable ETL pipelines to transform raw data into actionable, real-time insights.
English
Fluent
French
Native or bilingual
Experience
- BNP Paribas CIBAI & Data-Driven Solutions ScientistBANKING AND INSURANCESeptember 2021 - Today (4 years and 9 months)Paris, FranceDesigned and deployed AI-powered systems to strengthen financial risk detection and AML compliance.
- Data Pipelines : Architected and deployed high-performance ETL pipelines processing millions of transactions per day, ensuring data integrity, reliability, and real-time analytics.
- ML & GenAI : Developed Machine Learning and Generative AI models that improved transaction risk detection accuracy, enabling more proactive AML compliance and reducing false positives.
- RealTime Monitoring : Designed automated monitoring and alerting systems, allowing early detection of anomalies and supporting dynamic, risk-aware decision-making.
- Data Strategy Development : Partnered with business teams to define data strategies and optimize decision-making workflows, translating complex data into actionable insights.
Relevance to Your Needs:This experience at BNP Paribas demonstrates my ability to develop and implement advanced AI systems, including Generative AI models and high-performance data pipelines, in highly regulated environments. I specialize in delivering solutions that are not only compliant but also scalable, efficient, and impactful.Whether you're looking to :- Leverage Generative AI to drive creativity, enhance automation, or solve complex business challenges.
- Build real-time data pipelines for high-volume transactions and actionable analytics.
- Optimize workflows with cutting-edge machine learning models for predictive insights, anomaly detection, and decision-making support.
I can help you translate complex data into actionable insights, accelerate your workflows, and ensure your AI solutions are aligned with your strategic objectives, delivering measurable business impact. - Data4RiskData Scientist & Machine Learning EngineerTECHJanuary 2021 - August 2021 (7 months)Paris, FranceLed the development of a predictive platform to improve underwriting decisions and risk assessment.
- Risk Indicator Modeling : Generated actionable risk scores from crime, socio-economic, and property data.
- Computer Vision Innovation : Automated property feature extraction from satellite and Street View imagery, reducing manual assessment time and boosting risk scoring precision.
- ML Platform & Deployment : Engineered a production-grade ML pipeline with automated training, versioning, deployment, and monitoring to streamline AI operations.
Relevance to Your Needs:This experience demonstrates my ability to develop and deploy advanced AI solutions for predictive modeling, risk assessment, and computer vision applications. I specialize in creating scalable, high-performance AI systems that streamline operations, improve accuracy, and generate actionable insights.Whether you're looking to:- Build predictive platforms to enhance underwriting decisions and risk scoring.
- Develop risk models from diverse data sources (e.g., crime, socio-economic, property etc).
- Automate property feature extraction using computer vision techniques from satellite and Street View imagery.
- Engineer production-grade ML pipelines for automated deployment and continuous improvement.
I can help you optimize workflows, enhance decision-making, and deploy AI solutions that align with your business objectives, driving measurable impact. - NTN-SNR RoulementsData ScientisLOGISTICS AND SUPPLY CHAINJune 2020 - August 2020 (2 months)Annecy, FranceBuilt a real-time Computer Vision system for defect detection, driving major gains in quality control.
- Model Training & Optimization: Trained and fine-tuned CNN models, achieving high defect classification accuracy and reducing human inspection errors.
- Operational Impact: Validated the potential to reduce inspection time by ~85% and defect-related errors by $~40% during a 2-month trial handling ~1000 pieces per day.
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Education
- Computer Science and Applied Mathematics EngineerGrenoble INP - Ensimag2021I am a graduate of ENSIMAG in Grenoble, holding an engineering degree with a specialization in Ingénierie des Systèmes d'Information. The program provided a strong foundation in computer science and applied mathematics, with a focus on information systems engineering. During the final year, I specialized in Data Science and Artificial Intelligence, building expertise in data analysis, machine learning, and AI system design. The program also covered topics such as algorithms, databases, software project management, and IT security. My education at ENSIMAG combined theoretical knowledge with practical, hands-on experience, equipping me for roles in Data Science, AI, and information systems management in a rapidly evolving tech landscape.
- MSc in Industrial and Applied Mathematics - Grenoble Data Science And Machine learningUniversité Grenoble Alpes2021I expanded my expertise with a double diploma in the MSIAM program at Grenoble Alpes University, focusing on advanced topics like Machine Learning, Natural Language Processing, Optimization, and Statistical Learning. Key courses included Vision, Audio, and Text Applications, GPU Computing, Optimal Transport, and Extreme Event Analysis. This program strengthened my skills in mathematical modeling, data analysis, and software development, providing a solid foundation for a career in data science and machine learning. I gained practical experience in real-world applications, from image analysis to statistical modeling, empowering me to solve complex challenges with both theoretical rigor and practical solutions.