I built and evaluated credit-default models on 37,408 loan records using Python and scikit-learn, identifying factors behind default risk and translating the findings into credit-scoring recommendations. In my Online Retail Analysis project, I cleaned and analysed transaction data with Python and SQL, uncovering a customer segment that accounted for 51% of revenue.
As a Mathematics Teacher and Private Tutor, I analyse student performance data and turn it into clear progress reports and actionable feedback. I also assessed children’s-services outcomes using statistical tests and presented three evidence-based recommendations in an 18-slide report.
