Sana Ghazi

Sana Ghazi is a seasoned machine learning engineer with experience in developing predictive models and operational research solutions. At BNY Mellon, Sana served as a Lead Developer, creating models to enhance operational resiliency and predict government debt transaction failures using large datasets. Subsequent roles at Demandbase and CircleUp involved managing and deploying end-to-end machine learning models, specifically for unstructured data. Additional experience includes tutoring calculus at Carnegie Mellon University and working on complex mathematical algorithms for collateral management. Sana holds a Bachelor of Science in Computational and Applied Mathematics from Carnegie Mellon University and has completed coursework in mathematics at Universidad Carlos III de Madrid.