Projects

Bozeman Housing Price Prediction Project in Python

Housing Price Predictor Project

• Cleaned and engineered features from messy real estate listings, including categorical encoding and location-based features.
• Built and tuned machine learning models (Random Forest, XGBoost) to predict housing prices with an R² exceeding 0.81.
• Identified key pricing drivers such as living area, home type, number of bedrooms/bathrooms, and geographic coordinates

Personal Spotify Data Analysis and Visualization

Spotify Data Analysis Project

• This project used a collection of my personal Spotify data dating from February 2021 to January 2025 to collect insight into artist and listening trends.
• The analysis was performed using Jupyter Notebook for data cleaning and manipulation, while Tableau was used for interactive dashboards and visual storytelling.

MLB Linear Regression Modeling in R

MLB Linear Regression Project

• This project used MLB statistics from the 2000 to 2015 seasons sourced from Baseball Reference. The individual season statistics were combined to create a complete data set.
• The data was applied to form a regression model predicting season win percentage using season-long statistics, such as hits, runs, home runs, ERA, and run differential.

Achievements

• National Merit Scholar
• DataCamp Data Analyst Associate Certification

Education

• Data Science, BS (2023-2027)