Research into how educational mobility has changed in Canada with GaussX statistical software and Python- Preprocessed data, Newton-Raphson method to optimize ordered probit coefficients- Gaussian Mixtures to account for unobserved heterogeneity- Tested our results against Shorrocks mobility index and confirmed our findings

Visualized survey data in tableau

Assisted in setting up fraud dashboard for combined org, reviewed and improved KYC processes, optimized rules in check-fraud detection platform

Programmed algorithmic trading bots to maximize P&L in Market Making and CAPM casesMarket Making: Modeled order book fill probabilities to maximize expected value of algorithms limit order placements- Simulated parameter values for optimization as there was no relevant training data- Managed trend risk by conditioning models volatility expectations inversely on time since trade CAPM: Parsed risk free rate and expected price of an underlying ETF from recurring news bulletins - Valued securities by calculating covariance/variance for beta, bought and sold based on absolute expected return

Represented uni at Rotman International Trading Competition as a trader and our only programmer across all 6 cases Electricity: Overall most profitable trader by analyzing the electricity futures market and accurately predicting the long/short imbalance in next period spot marketsOptions: Valued and traded options with Black Scholes, managed Delta to stay below the specified limitCommodities: Coordinated with refiners and producers on team to profitably trade oil futuresTenders: Received tender offers, evaluated market price and liquidity to exit position

Helped startup improve computer vision models, worked on Salesforce integration

french political science competition