Freelancer profile translated to English.
Back to original languageAbout Jacques
Graduated with a Master's in Applied Mathematics (Financial Mathematics, AI, Statistics) from Université Paris-Dauphine, I offer my services as aData Scientist, Machine Learning Engineer, Computer Vision Engineer.
For 3 years, I have been assisting my clients indeveloping Machine Learning and Deep Learning models, from research to deployment.
🎯Areas of Expertise🎯
- **Computer Vision**: **object detection**, **segmentation**, **regression, classification, GANs, Vision-Transformers, and diffusion models**.
- **Remote Sensing**: geospatial data, radar (SAR) and optical satellite imagery, GIS.
🛠️Technologies and Frameworks🛠️
- Programming Languages: 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