Summary
Isaac Rivera is a senior credit risk data scientist based in Lima with eight years of experience building predictive models, IFRS 9 provisions, and production-ready data pipelines for financial institutions. He combines hands-on expertise in Spark, Python, SQL and Azure with practical data engineering skills—Airflow, Docker/Kubernetes and Linux administration—to move models from development into cloud and on-premise production. At Caja Arequipa he has led ECL implementations (PD, LGD, EAD) and automated financial reporting, demonstrating both quantitative rigor and operational delivery. Currently deepening his quantitative finance credentials through a WorldQuant MSc and advanced analytics coursework, he brings a rare mix of mechatronics-trained systems thinking and finance-focused modeling. Colleagues describe him as “a man on many missions” who balances analytical precision with pragmatic automation to reduce risk and improve decision-making.
8 years of coding experience
2 years of employment as a software developer
Msc. Economics, Econometrics and Quantitative Economics, Msc. Economics, Econometrics and Quantitative Economics at National University of Engineering
Msc. in Financial Engineering, Quantitative Research, Msc. in Financial Engineering, Quantitative Research at WorldQuant University
Programa de Especialización, BIG DATA & ANALYTICS, Programa de Especialización, BIG DATA & ANALYTICS at Universidad Nacional de Ingeniería
Especialización en Finanzas, Finance, General, Especialización en Finanzas, Finance, General at Equilibrium Financiero
Spanish, English