Evan is a data scientist with a passion for uncovering meaningful insights through statistical analysis and innovative modeling. He has experience using Python, SQL, and R across a wide range of tasks, including machine learning, web scraping, and econometrics. He holds a B.A. in Quantitative Economics and is currently pursuing a Master’s in Applied Economics at the University of San Francisco. In his free time, Evan builds machine learning models for sports betting using time series approaches. He also explores directional algorithmic trading and develops options strategies that leverage spread techniques, Monte Carlo simulations, and the Black-Scholes model for pricing and risk analysis.