03Experience
University of Toronto Engineering Finance Association
Sales & Trading Analyst
Combined quantitative modeling with market education, building a 22-factor XGBoost model for a 50-participant competition.
Sep 2025 – Apr 2026On-site
Previously Portfolio Manager (Feb 2026 – Present)
- Python
- XGBoost
- Pandas
- NumPy
- Feature engineering
- Model evaluation
- CAPM
- Yield curves
Contributions
- Built a 22-factor XGBoost model for a 50-participant competition using macro, rates, momentum, and volatility features.
- Applied feature engineering and model-evaluation concepts to a financial research setting.
- Studied and used CAPM, yield curves, bond pricing, and options-pricing concepts.
- Explored optimization, transaction-cost analysis, and regime-aware risk.
- Communicated market views and model assumptions in a team environment.
Overview
Built a 22-factor XGBoost research model and developed market, fixed-income, options, optimization, and transaction-cost analysis through UTEFA.
Measured outcomes
22
Modeled factors
Feature count of the competition model as reported in the current resume.
50
Competition participants
Competition size as reported in the current resume.
Tools & stack
- Python
- XGBoost
- Pandas
- NumPy
- Feature engineering
- Model evaluation
- CAPM
- Yield curves
- Bond pricing
- Options pricing
- Transaction-cost analysis
Scope of this page
- Student competition and educational research; no claim of live trading, investment advice, or profitable performance.
- No competition placement, return, predictive accuracy, alpha, or trading profit is published, because none was verified.