MS Business Analytics & Information Management candidate at the University of Delaware (GPA 3.8, graduating May 2026), with a background that spans civil engineering, psychology, and data analytics. I bring 4.5 years of real-world project experience and a genuine curiosity for turning unknown into known.
I work at the intersection of data, business, and human behavior β using analytics to solve problems that actually matter to organizations. My focus areas:
- Insurance & Risk Analytics β predictive modeling, claims analysis, pricing
- Finance & Business Intelligence β dashboards, regression, KPI reporting
- Real Estate & Infrastructure Analytics β market analysis, cost modeling
- Research & Qualitative Analysis β Gioia methodology, interview coding
Languages: Python, SQL, SAS
Visualization: Power BI, Excel
Methods: Machine Learning, Regression, Decision Trees, Naive Bayes, Monte Carlo Simulation, Data Cleaning
Other: NetLogo (Agent-Based Modeling), Jupyter Notebooks, GitHub
| Project | Tools | Description |
|---|---|---|
| Auto Insurance Risk Prediction | Python | Decision Tree & Naive Bayes to predict at-fault accident risk for State Farm |
| NYC Water Billing Analysis | Power BI, SQL | Identified billing anomalies across 14K+ records; regression analysis of overcharging patterns |
| COVID-19 Geographic Trend Analysis | SAS | Multi-region spread analysis using PROC SQL, SGPANEL, and heat maps |
| Monte Carlo Simulation | NetLogo, Python | Agent-based simulation modeling using the Law of Large Numbers |
MS, Business Analytics & Information Management β University of Delaware (2026)
MA, Psychology
B.Tech, Civil Engineering