"Creative data scientist with strong fundamentals in machine learning, software engineering, and AI development. Shows high upside in predictive modeling and full-stack development environments, with a knack for data visualization and clear communication."
Game Film
Highlight reel of key projects and technical work
SMT Data Challenge
Developed a machine learning pipeline on MiLB tracking data to model baserunning with logistic regression and optimize cutoff play decisions with a Random Forest classifier, visualized through an interactive dashboard.
NFL Wordle
Built an interactive NFL guessing game inspired by Wordle, challenging players to identify NFL players based on attributes like team, position, and stats. Features dynamic feedback and player database integration.
NFL Big Data Bowl
Utilized XGBoost to model NFL tracking data, assigning tackle probabilities to plays to develop a new 'Tackle Rate over Expectation' metric. Commended by NFL analytics departments for quality of visualizations.
Fire-Ready Forests
Used Aerial and Terrestrial Laser Scanning data to build 3-D Canopy Height Models, generate engineered treelists, and train ML models to predict tree species and forest attributes for wildfire simulation.
Power Outage Analysis
Built a Random Forest Regression model with scikit-learn to analyze a dataset of power outages, used techniques like one hot encoding, hyperparameter tuning, and cross-validation to optimize model predictions.