I'm a Data Scientist with a Master's in Data Science from Merrimack College specializing in end-to-end ML pipelines, fairness-aware modeling, and large-scale data analysis. My projects work with real-world datasets — 16M+ row U.S. Census data, 4.25M HMDA mortgage applications, and 941K NYC 311 service requests. I build in Python, SQL, and R, deploy dashboards in Tableau and Power BI, and hold an AWS Cloud Practitioner certification. Background in legal operations and data governance. Currently seeking entry-level Data Scientist roles.
- 🛒 ReviewPulse — Agentic AI Consumer Insight System — Autonomous LLM agent (Claude tool use) that investigates product review data, detects statistically significant defect trends via spike detection, and generates evidence-backed action reports; includes a Streamlit dashboard with an interactive Q&A assistant grounded in the same agent tools
- 🫀 Heart Disease Classification Pipeline — End-to-end SparkML pipeline on real UCI Cleveland data; feature engineering, 4-model comparison (Random Forest, GBT, LR, Decision Tree), MLflow experiment tracking, and CrossValidator hyperparameter tuning; best model AUC 0.877
- 🏦 Home Loan Approval Prediction — ML pipeline on 4.25M real HMDA 2023 mortgage applications; XGBoost ROC-AUC 0.9932, 96.3% accuracy across 121 features
- 🏠 Rent Burden Prediction — Fairness & ML analysis on 16M+ ACS PUMS household records (Logistic Regression, Random Forest, Gradient Boosting); equity analysis across race, sex, and geography for HUD policy context
- 🗽 NYC 311 + Weather Correlation Dashboard — Production-grade ETL pipeline ingesting 941K real NYC civic complaints + NOAA weather data via REST APIs; cleaned with Python & PostgreSQL, visualized in an interactive 5-tab Power BI dashboard with automated daily refresh. Live Dashboard
