Summary
Perfect Gidisu is a credit risk data scientist and final-year PhD candidate in Applied Mathematics with eight years of experience applying predictive modelling, machine learning and data-driven research across banking, fintech and academia. She has built production-grade credit risk models and customer-segmentation algorithms at ING and Gimme5, and now brings that expertise to Booking.com, pairing rigorous quantitative methods with business-focused impact. Her background spans quantitative finance (MSc, Milan and exchange at Peking University), economics and internal audit, giving her a rare blend of model development, governance and domain insight. Known for lateral thinking and rapid learning, she has taught and mentored students while translating complex statistical ideas into actionable products for risk and marketing. An accomplished researcher, she leverages high-performance analytics and innovative data sources to extract predictive signals often overlooked in standard credit models.
8 years of coding experience
7 years of employment as a software developer
Bachelor of Arts - BA, Economics and Political Science, Bachelor of Arts - BA, Economics and Political Science at University of Ghana
Master's degree Exchange Program, Quantitative Finance, Master's degree Exchange Program, Quantitative Finance at Peking University HSBC Business School
ACCA
University of Milan
Doctor of Philosophy - PhD, Applied Mathematics, Doctor of Philosophy - PhD, Applied Mathematics at Eindhoven University of Technology