Second-year Computing Science student with hands-on experience in data engineering and a strong foundation in banking and finance, specializing in credit reporting, risk, originations, and collections. My work with collections and financial credit risk teams at large banks and providers has equipped me with deep insights into leveraging data for strategic decision-making. Skilled in ETL processes, big data analysis, and database management, I am eager to contribute to MasterCard's mission of powering secure, innovative, and inclusive financial ecosystems through advanced data solutions.
ETL Pipeline for Credit Risk Analysis: Designed and implemented an ETL pipeline to extract, transform, and load large datasets from multiple sources into a database for credit risk modeling.
Collections Strategy Optimization: Built scenario calculators for debt collection agency (DCA) allocations, recovery rates, and KPI optimization, enabling better strategic modeling for financial institutions.
Big Data Analysis with Spark: Processed and analyzed datasets using Apache Spark to derive actionable insights for hypothetical client scenarios.
Dynamic Backend System Development: Built a Python-powered backend for a website that collects, validates, and processes user inputs to interact securely with a MySQL server. Ensured robust data handling and security protocols throughout the project life cycle.
Simple Neural Network From Scratch: Wrote a simple Neural Network from scratch to play pong against itself. Created working implementation of a network and genetic training algorithm with minimal outside influence or directive.
As an Australian-Canadian dual citizen studying at the University of Alberta, I embraced the challenge of moving across the globe to pursue my education, fostering independence and adaptability. My experiences have enabled me to work effectively with individuals from diverse cultural and professional backgrounds, bringing a global perspective to my academic and technical projects.