Data Scientist (MSDA) • Product & Healthcare Analytics • MLOps-curious
I build end-to-end analytics: data pipelines → modeling → decision storytelling.
Highlights
- 🧪 Wine Quality ML: Random Forest hit ~78% test accuracy; feature importance drove model insights.
- 🌐 Portfolio site with resume & case studies (GitHub Pages).
Tech: Python, SQL, R, scikit-learn, XGBoost, dbt (learning), Tableau/Power BI
Where to start
- Wine Quality Capstone
- Portfolio site (GitHub Pages):
Connect: LinkedIn