Projects
Applied Statistics & Healthcare Analytics
NHANES Statistical Inference
Moved beyond descriptive statistics to perform rigorous population-level inference on NHANES healthcare data. Validated the Central Limit Theorem empirically and applied hypothesis testing to quantify health risks across demographic groups.
Impact: Replaced uncertainty with statistical confidence, delivering clear evidence-based insights on blood pressure and body weight trends to support public health analysis.
- Python
- Pandas
- Statistical Inference
- Hypothesis Testing
- Seaborn
Business Intelligence & Financial Risk
Loan Default & Risk Analytics
Designed a scalable Power BI solution for risk assessment on 250,000+ loan records. Engineered an end-to-end pipeline using SQL Server and On-Premises Gateway to ensure real-time data accuracy, implementing complex DAX logic for financial KPIs.
Impact: Enabled stakeholders to instantly identify high-risk applicant segments and monitor YOY default trends, transforming static reports into a dynamic decision-support system.
- Power BI
- SQL Server
- DAX
- Data Modeling
- Dashboard Design
Predictive Modeling & Geospatial Analysis
SpaceX Falcon 9 Landing Prediction
Analyzed mission-critical launch data to predict first-stage landing success. Prioritized model interpretability and evaluation metrics (Recall/F1) to address class imbalance, ensuring reliable performance prediction where false negatives carry high costs.
Impact: Translated technical model outputs into intuitive geospatial visualizations, providing non-technical stakeholders with a clear understanding of the key factors driving launch success rates.
- Python
- Scikit-Learn
- Geospatial Analysis
- Classification Metrics
