Quant Developer | C++ / Python Software Engineer
Engineer from École Centrale de Lyon and Pontificia Universidad Católica de Chile, with experience building production software and data tools supporting trading operations at Capital Fund Management (CFM) in Paris.
My technical work is centered on C++ and Python, with a focus on software engineering, machine learning, quantitative finance, and data-intensive systems.
C++17 implementation of classical machine-learning algorithms and supporting tooling using Eigen.
- Linear and logistic models, tree ensembles, k-NN, linear SVM, Naive Bayes
- PCA, KMeans, perceptron, and a minimal neural-network implementation
- Preprocessing, cross-validation, evaluation, and hyperparameter sweeps
- Real-data workflows with Python/Jupyter verification
C++23 repository for implementing and studying core data structures and algorithms, combining CLRS-based study with coding-interview practice.
- Trees, graphs, dynamic programming, greedy algorithms, shortest paths, and related topics
- Tested implementations with CMake and Catch2
- Focus on algorithmic reasoning and modern C++
Event-Driven Backtesting Engine — C++23
Developing an event-driven backtesting engine for systematic trading strategies, with deterministic historical-data handling, explicit market/signal/order/fill events, portfolio accounting, and reproducible execution.
- Programming: C++, Python, SQL, TypeScript
- Machine Learning: Eigen, NumPy, Pandas, scikit-learn
- Software Engineering: CMake, Git, Docker, FastAPI, Angular, PostgreSQL
- Quantitative Finance: probability & statistics, derivatives, fixed income, market microstructure, portfolio & risk
- Capital Fund Management (CFM) — Quant Developer Intern, IT Middle Office
- École Centrale de Lyon — Master of Science in General Engineering
- Pontificia Universidad Católica de Chile — Mechanical Engineering, with distinction