Software developer specializing in Python, data analysis, and quantitative trading systems. Former travel agent who taught himself to code — shipped 7 real projects including a quantitative trading system and 3 live deployments.
I spent years as a travel agent — coordinating logistics, managing complex itineraries, and solving problems under pressure. Good skills, wrong industry.
I started teaching myself to code because I wanted to build things, not just use them. What began with Python scripts quickly evolved into data analysis, API integrations, and eventually a full quantitative trading system for prediction markets.
I didn't take the traditional path into tech. I took the harder one — self-taught, project-driven, learning by building real systems that actually work. That's the kind of developer I am: resourceful, relentless, and always shipping.
Managing logistics, complex itineraries, and client relationships across multiple time zones. Built sharp problem-solving skills under real pressure — coordinating dozens of moving parts daily.
Dove into Python, data analysis, and APIs. No bootcamp, no hand-holding — just docs, projects, and late nights. Learning by building, not by watching tutorials.
Built a prediction market paper-trading engine (4,800+ lines, 57 tests), a full-stack aviation analytics platform with real backend, a Montreal housing data pipeline with 5 visualizations, an interactive Streamlit dashboard, and an automated job scraper. Real code, real systems.
20,000+ lines of code (Python + TypeScript), 70+ automated tests, CI/CD pipelines, Docker containers. Seven shipped projects on GitHub — including a multi-exchange paper-trading system, a full-stack aviation analytics platform, and a prediction market research engine. Looking for the right team to grow with.
Multi-exchange paper-trading research system with 7-layer validation architecture. Targets Hyperliquid (perpetual futures) and Polymarket (prediction markets) with adaptive learning, 3-stage governance, circuit breakers, and human oversight. 16,000+ lines of Python across 11 core scripts, 29 test files, real-time data integrity validation, and comprehensive audit trails. CI-backed research repository — paper trading only, no live execution.
Paper-trading research engine for prediction markets — 14 strategies, market ingestion, risk-constrained execution simulation, backtesting, and Streamlit dashboard. 70 tests, strict typing, CI/CD. Try it live →
Aviation intelligence platform with route competitiveness analytics — real FastAPI backend with PostgreSQL/CSV data modes, Next.js frontend, route change detection, airport role metrics, and competition analysis.
Destination-first flight deal discovery with value scoring across 26+ destinations. Next.js frontend with animated UI, region filters, and deal ranking. FastAPI backend with Kiwi/Amadeus API clients. Try it live →
Data analysis of Montreal's rental and sales market — statistical modeling, affordability metrics, and 5 visualizations generated from a full data pipeline.
9 interactive Plotly charts visualizing rental trends, affordability, and vacancy across Montreal boroughs. Synthetic data modeled on CMHC market ranges. Dark theme, Dockerized, deployed on Streamlit Cloud. Try it live →
Automated job scraper that pulls from multiple boards via async requests, deduplicates with SQLite, and generates daily markdown digests.
A Flask-based community platform for queer digital nomads to share travel experiences. Features user authentication, database integration, and responsive UI. Built as a CS50 final project at Harvard.