At Team Soft LLC, I analyzed shipment budgeting and financial data, comparing budgeted and actual costs to identify cost variances and pricing opportunities. I developed Power BI dashboards tracking financial performance, revenue by country, agent payouts, budget variance, and claims trends.
I also cleaned and validated datasets and created calculated fields to improve reporting reliability. My analysis supported operations and finance teams with agent selection, pricing, and claims-prevention decisions.
For my M.S. capstone at Trine University, I analyzed a $2.3M retail dataset across 50 U.S. states and built Tableau and Power BI dashboards. I translated the findings into seven business recommendations.
My data science projects include a Random Forest model for predicting the Urban Water Quality Index and machine learning work in fraud detection, spam detection, customer churn, and computer vision. I use Python, SQL, and analytics tools to turn data into models, dashboards, and findings.
