At Introba, I collected, cleaned, and preprocessed sustainability and building performance datasets using SQL and Excel. I also performed exploratory data analysis, optimized SQL queries, and applied machine learning models to identify trends and predictive insights.
For my Credit Risk Prediction & Financial Risk Analysis project, I analyzed 30,000 credit card records and trained, evaluated, and optimized multiple models. I also conducted Expected Loss analysis, stress testing, and Monte Carlo simulations, then built a Power BI dashboard to visualize risk and scenario analysis.
I developed projects to predict Boston housing prices and flight ticket prices, applying regression and tree-based models. The flight price project achieved an R² score of 0.816 and MAPE of 13.21%.
I'm participating in the SITA AI Engineering Bootcamp, developing practical skills in Python, API integration, Retrieval-Augmented Generation, and AI-powered applications. I hold a B.Sc. in Applied Information Technology and am pursuing an M.Sc. in Information Technologies and Systems.
