About Jacques
Diplômé d'un Master en Mathématiques Appliquées (Mathématiques Financières, IA, Statistiques) de l'Université Paris-Dauphine, je propose mes services en tant que Data Scientist, Machine Learning Engineer, Computer Vision Engineer.
J'accompagne mes clients depuis 3 ans dans le développement de modèles de Machine Learning et Deep Learning, de leur recherche à leur déploiement.
🎯 Domaines d'expertise 🎯
- Computer Vision : détection d'objects, segmentation, régression, classification, GAN, Vision-Transformers et models de diffusion.
- GenAI : LLM/RAG, NLP, Knowledge Graphs, ChatBot
- Forecasting, Mathématiques Financières
- Déploiement, mise en production et maintenance des modèles (MLOps, CI/CD, LLMOps)
- Création de pipeline complexe de données et mise en production
- Automatisation et parallélisation de code
- Remote Sensing : données géospatiales, images satellites radars (SAR) et optiques, GIS.
🛠️ Technologies et frameworks 🛠️
- Langage de programmation : Python, PySpark, C, C++, Java, R, SQL, SPARQL, Bash (Unix shell), VBA
- Data Science / ML : Python, PyTorch, TensorFlow, Spark, Elasticsearch, Lightning, ClearML, OpenCV, Scikit-learn, LlamaIndex, LangChain, NEO4J, Multiprocessing, NumPy, SciPy, Pandas, Matplotlib, Selenium, AutoML, H2O, Flask API
- Generative AI : ChromaDB, Azure, AWS Bedrock, NVIDIA NIM, OpenAI Services
- Software / Cloud : AWS Ecosystem, Git, Jira, Azure, GCP, Docker, Kubernetes, Jupyter, Eclipse, VSCode, Travis CI (DevOps)
- Scrapping / NLP : NLTK, Selenium, BeautifulSoup
- GIS : QGIS, ArcGis
French
Native or bilingual
English
Native or bilingual
Spanish
Fluent
Can work on-site
Paris (up to 50km), Nice (up to 50km), Lille (up to 50km), Strasbourg (up to 20km), Toulouse (up to 50km)
Experience
- SARP - VEOLIAData Scientist Freelance - Computer Vision, GenAIENERGY AND UTILITIESApril 2024 - Today (2 years and 2 months)- Development of Real-Time Multi-Object anomaly detection system for wastewater networks (End-to-End POC)
- ASTERRADATA SCIENTIST | DEEP LEARNINGTECHNovember 2022 - March 2024 (1 year and 5 months)
- Leading EarthWork AI product : Assess underground moisture conditions for multiple applications including PoC, MVP, Product-market fit - collaboration with different teams and executive levels
- R&D of SOTA Deep Learning algorithms applied on Synthetic-aperture Radar satellite imagery and geospatial datasets : Self-Supervised Learning (Vision Transformers, Masked Autoencoders, UNets), Survival Analysis
- Successfully developed the most accurate AI algorithm for Soil Moisture estimation at ASTERRA, now sold as part of the new SaaS
- Albo ClimateData Scientist | Deep Learning EngineerENVIRONMENTALOctober 2021 - July 2022 (10 months)
- Responsible for developing Deep Learning and Machine Learning models for predicting carbon sequestration maps (Above Ground Biomass, Soil Organic Carbon) from optical and SAR satellite imagery for the purpose of creating Carbon Credits
- Geospatial data engineering, analysis, display, development and improvement of SOTA DL models (conditional GAN, DeepLabv3+, Ensemble methods), ETL construction
- Successfully developed the best models for Soil Organic Carbon and Above Ground Biomass estimation, main company product
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Education
- Master of Science - MS (280), Applied Mathematics Statistics, Data Science & Financial MathematicsUniversité Paris-Dauphine, PSL2021Master of Science - MS (280), Applied Mathematics Statistics, Data Science & Financial Mathematics
- MS Exchange Student, Artificial Intelligence & Data ScienceUniversiteit Maastricht2020MS Exchange Student, Artificial Intelligence & Data Science