I analyzed 38,000+ loan records in my Bank Loan Analysis project, using SQL and PostgreSQL to calculate portfolio KPIs and track month-to-date and month-on-month metrics.
I segmented good and bad loans and compared interest rates and debt-to-income ratios to assess risk. I also used loan issue dates, employment length, and state to surface trends.
For my SMS Spam Classifier project, I built a model that classified 5,000+ messages as spam or ham with 97%+ accuracy. I compared Naive Bayes and Random Forest, then deployed an interactive Streamlit app for real-time predictions.
My experience also includes site training at Heeth Constructions, monitoring work on the New Archies Court Extension, and an internship with NHAI's PIU, where I supported site monitoring and technical documentation for the 4-Lane Connector Project.
