Open to opportunities

I build systems that

Software developer specializing in Python, data analysis, and quantitative trading systems. Former travel agent who taught himself to code — built 10 shipped projects including a quantitative trading system.

From booking flights to
building trading bots.

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.

24,000+
Lines of Code
across 8 projects
14
Trading Strategies
backtested & validated
59
Tests Passing
automated test suite
100%
Self-Taught
project-driven learning

The Journey

01

Travel Agent

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.

02

Self-Teaching Phase

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.

03

First Real Projects

Built a prediction market trading bot (4,800+ lines, 58 tests), 4 specialized trading agents using The Agency framework, a full-stack aviation analytics platform with modern UI, a Montreal housing data pipeline with 5 visualizations, an interactive Streamlit dashboard, and an automated job scraper. Real code, real systems.

04

Ready for Tech

24,000+ lines of production code (Python + TypeScript), 72+ automated tests, CI/CD pipelines, Docker containers. Ten shipped projects on GitHub — including 4 specialized trading agents using The Agency framework, a full-stack aviation analytics platform, and a quantitative trading bot with live API integration. Looking for the right team to grow with.

Featured Work

Trading Agency Agents 🆕 NEW

4 AI trading agents orchestrated via The Agency framework. Bull/bear debate module scores every signal before execution — bull and bear analysts argue the trade, low-confidence signals are blocked automatically. Live signal pipeline: Hyperliquid funding scanner → debate gate → risk manager → execution. 14 tests, CI/CD.

Python The Agency Quant CI/CD

Flight Price Intelligence Lab 🔴 LIVE

Full-stack aviation analytics platform with route intelligence scoring (0-100), price alerts, and interactive Recharts dashboards. Built with Next.js 14 + FastAPI + PostgreSQL. Designed to process BTS flight data. Try it live →

Next.js FastAPI TypeScript PostgreSQL

Flight Discovery Platform

Full-stack flight deal discovery with an intelligent scoring algorithm — 58 flights, 26+ destinations, Google Flights booking, animated UI with framer-motion, region filters, and deal scoring. Next.js frontend + FastAPI backend.

Next.js FastAPI TypeScript Full-Stack

Montreal Housing Analysis

Data analysis of Montreal's rental and sales market — statistical modeling, affordability metrics, and 5 visualizations generated from a full data pipeline.

Python pandas seaborn Data Analysis

Montreal Housing Dashboard 🔴 LIVE

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 →

Python Streamlit Plotly Docker

Job Hunter

Automated job scraper that pulls from multiple boards via async requests, deduplicates with SQLite, and generates daily markdown digests.

Python httpx SQLite Automation

QueerNomads

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.

Python Flask SQLite Full-Stack

Hyperliquid Funding Analyzer

Scans 229 perpetual markets every 4 hours via cron, flags funding anomalies (>0.03%) for arbitrage. Live pipeline identified ZETA at -473% annualized funding on day one. CLI + JSONL logging + automated signal alerts.

Python DeFi API Quant

Cross-Market Signals

Signal detection system correlating Polymarket prediction events with Hyperliquid perpetual futures — SQLite time-series storage, automated data collection.

Python SQLite Data Pipeline Quant

Canada Housing Intelligence

National housing intelligence platform — automated data collection, interactive Folium maps, trend analysis, and affordability metrics across Canadian markets.

Python Folium pandas Data Analysis

What I Work With

Languages & Core

Python
JavaScript
HTML / CSS
SQL
Bash

Data & Analysis

Pandas
NumPy
Data Visualization
Statistical Analysis
Backtesting

Tools & Infrastructure

Git / GitHub
REST APIs
Linux / CLI
VS Code
CI/CD

Domain Knowledge

Quantitative Trading
Prediction Markets
Finance / Risk
Automation
System Design

Articles

How I Built a Quantitative Trading Bot as a Self-Taught Developer

My journey from travel agent to building a 3,600-line algorithmic trading engine — what I learned about async I/O, strategy design, backtesting, and production-grade architecture.

Let's connect.

I'm actively looking for opportunities in software development, data analysis, and quantitative trading. If you're building something interesting — let's talk.