my background and things i have done

Projects

Delta Neutral Yield Farming Trading Strategy 17.37% return over 4 months, SPX return over the same period was 3%; Sharpe Ratio: 5.43

Created a fully systematic strategy based on delta hedged liquidity provision on Ethereum and Solana
Wrote modules in Python using Web3.py to read and analyze on-chain data to determine hedging size through valuing LP tokens for each address by calculating the number of constituent tokens in each LP token
Wrote a margin management module to remain margin compliant with hedges as well as using excess cash to reinvest into the strategy by minting new LP tokens and auto-compounding the liquidity provision rewards
Used Cron jobs to record PnL and created an interface using Telegram to monitor performance and handle errors

Neo Financial Junior Data Scientist - Enterprise Data Science

Developed an XGBoost model to predict charge-off likelihood for early month-on-book customers (<6 months), targeting a cohort loss rate of 30% and saving $4 -$ 6M annually by reducing contained losses
Built a RAG-based transaction enrichment application, automating metadata matching for 6M+ transactions monthly, eliminating 14 FTE hours and delivering $600K in annual value through accurate rewards distribution

CPP Investments (CPPIB) Software Engineering Intern - Quantitative Strategies - Volatility Risk Premia

Built Python programs to decompose daily profit/loss based on option exposure across FX, rates, and credit books, improving calculation time by 12.0% by vectorizing calculations using numpy saving one hour of time
Analyzed the effectiveness of implementing different long volatility strategies in the USD rates book as a diversification factor to the portfolio, decreasing delta-hedge cost by 3.5%, saving $3.8M per year
Created a command line interface using Click to reconcile commodity volatility portfolio positions between two books of record which reduced the time to reconcile the books by over 2000% saving one hour per day

Western University Research Assistant – 4/2 Stochastic Volatility Model

Simulated a Cox-Ingross-Ross (CIR) process with direct sampling using Python; built a program to estimate parameters for the CIR Process to fit realized prices of VVIX through Maximum Likelihood Estimation
Developed new parameter estimation methodology for the CIR Process offering a 5% improvement over previous MATLAB solution from prebuilt optimization functions thereby saving thirty-five minutes per run
Converted entire code-base from MATLAB to Python, increasing processing speed of stochastic process simulations and calculations by 34% through numpy vectorized implementations of the equations

Mustang Capital Derivatives Vertical Lead – Student Investment Fund

Trained a 3-state Hidden Markov Model (HMM) using a custom walk-forward cross validation method with intraday VIX and SPX data to determine and label volatility and market regimes
Led a five person team to build an end-to-end data processing pipeline using Python scripts to download and insert data into a MySQL database; wrote scripts to clean, process and transform data to features used in the model

Technologies: Python (Pandas, Numpy, Scipy, Sklearn, PyTorch, XgBoost), Rust, DBT, Snowflake R, MATLAB, SQL

Awards: First Place at Hack Western (1st/92 teams), Second Place at UW Datathon

Interests: Ultra Marathons, Triathlons, Bio Hacking, Texas Hold’em Poker, Street Photography

University of Calgary Master of Data Science and Analytics (4.00/4.00) Calgary, AB, 2023-2024

University of Western Ontario Bachelor of Honours Science - Mathematics, Statistics, and Computer Science (3.86/4.00) London, ON, 2018-2023

Relevant Coursework: Complex Analysis, Real Analysis, Numerical Analysis, Vector Calculus, Statistics & Probability, Discrete Mathematics, Linear Algebra, Data Structures & Algorithms, Mathematics for Machine Learning, Regression
Awards: Dean’s Honour List, NSERC Student Research Award ($8500)