Hi, I’m Samuel Guillot, a Data Scientist specializing in Machine Learning applied to quantitative finance.
I currently work at Crunch Capital, where I design predictive models and automated data pipelines for investment strategies.
My background combines finance (accounting, audit, banking) and advanced software engineering, developed through professional experience, my master degree CCA in accounting and 42 Paris.
My focus is on feature engineering, model evaluation, backtesting, and production-ready ML systems.
Here are a few of the technologies and skills I’m working with:
- Programming Languages: Python, C, C++, Javascript
- Machine Learning & Data: Pandas, NumPy, Scikit-learn, PyTorch, TensorFlow
- Web Development: HTML, CSS, React, Django, Next.js
- DevOps & Containers: Docker, AWS, Ansible
- Database: SQL, PostgreSQL, MySQL
- Others: Git, N8N
- Quantitative Research – Crunch Capital
- Feature engineering and ML models for market-neutral and momentum strategies
- Robust backtesting, performance analysis, and data pipelines
- Rental Scoring SaaS (2025)
- OCR extraction, document validation, scoring algorithm, cloud deployment (Next.js + AWS)
- GeoAI Hack Challenge – Finalist (2025)
- Satellite image analysis to detect locust breeding zones using AI
- ML From Scratch Projects
- Multilayer Perceptron (forward/backpropagation, gradient descent)
- Reinforcement learning agent (policy optimization)
Feel free to reach out to me via my LinkedIn Profile or with my email samuelguillot75@gmail.com.