Aspiring Data Scientist based in Waukesha, WI — currently completing the TripleTen Data Science Bootcamp (Sprint 11 of 17).
I come from an unconventional background: food service, retail, social work, and a B.S. in Criminology with a Psychology minor. That foundation gives me something most DS candidates don't — I know how to read people, understand systems, and ask the right questions before diving into data.
| Project | Description | Tools |
|---|---|---|
| Used Car Price Explorer | Live web app analyzing US vehicle listings and price drivers | Python, Plotly, Streamlit |
| Gold Ore Purification ML | ML models predicting gold recovery efficiency at industrial processing stages | Python, Scikit-learn, EDA |
| Beta Bank Churn Prediction | Classification models predicting customer churn with F1: 0.62, AUC-ROC: 0.86 | Python, Scikit-learn, Random Forest |
| Telecom Plan Revenue Analysis | Statistical analysis of 500 customers to recommend advertising strategy | Python, SciPy, Hypothesis Testing |
| Video Game Sales Analysis | Regional market study across NA, EU, JP gaming markets | Python, Pandas, EDA |
| OilyGiant Well Location | Bootstrapping + regression to find optimal oil well drilling location | Python, Scikit-learn, Risk Analysis |
| Chicago Taxi SQL Analysis | SQL queries + hypothesis testing on taxi trip data and weather impact | Python, SQL, Plotly |
| Megaline Plan Recommender | ML classification model recommending best phone plan for legacy subscribers | Python, Random Forest, Decision Tree |
