Turning financial complexity and business data into models, systems, and actionable decisions.
I spent nearly a decade trading options and derivatives in one of the world's most volatile markets. That experience shaped how I think: probabilistic, data-driven, and always focused on what actually moves the needle.
My background in Business Administration gave me something most technical profiles lack — a deep understanding of how businesses work from the inside: their processes, inefficiencies, and what decision-makers actually need.
Today I combine both worlds — financial expertise and technical capability in Data Science, ML, and automation — to find and generate value where others don't look.
Languages
ML & Data Science
Visualization & BI
Cloud, DevOps & Tools
APIs & Integrations
| Project | Description | Stack |
|---|---|---|
| Algorithmic Trading — ML | ML signals for GGAL & NVDA. Bloomberg-style candlestick charts. | Python · sklearn · Plotly |
| Credit Risk & Scoring | PD modeling + client scoring + business rules for credit assignment | Python · sklearn · statsmodels |
| Market Risk — VaR & GARCH | Market risk analysis with GARCH volatility and backtesting on GGAL across crisis periods | Python · ARCH · Plotly |
| Argentina Economic Data Pipeline | BCRA, INDEC & Ministry of Economy pipeline with AI-powered PDF parsing | Python · APIs · OpenAI |
| Options Expiration Analysis | Probabilistic study of bimonthly option expiration cycles since 2000 | Python · Plotly · yfinance |
| Quantitative Market Regimes | HMM-based market regime detection, streaks and conditional probabilities on GGAL | Python · hmmlearn · Plotly |
| Financial Intelligence Bot | Multi-source financial intelligence platform with AI-generated reports via Telegram | Python · OpenAI · Telegram API |
| Private AI Transcriber | Local Whisper-based transcription app — privacy-first, no upload needed | Python · Streamlit · faster-whisper |
| Retail Stock Manager | Demand forecasting & inventory optimization for SMEs | Python · sklearn · Streamlit |
| S&P500 Regime Clustering | Unsupervised clustering of S&P500 market regimes by return and volatility | Python · sklearn · Plotly |
- 🎓 Business Administration — UNICEN (graduating 2026)
- 📊 Data Science Diploma — UADE (2022)
- 📈 Quantitative Finance & Portfolio Management — Matba Rofex School / BCR (2024)
- 🏦 Trusts & Investment Funds — UCEMA (2023)
- 🔐 CNV Capital Markets License (in progress — 2026)
- 🌐 Languages: Spanish (native) · English (C1-C2) · Italian (basic)
- Completing and polishing my quantitative finance project suite
- Building a GitHub Pages portfolio site
- CNV Capital Markets certification