Guillermo Sanchez is a data scientist at SFL Scientific. Guillermo has significant experience analyzing large datasets to improve data quality, creating financial regulatory reports and controls with the goal of reducing the operational risk for clients. He earned his Electrical Engineer and Computer Science degree at Universidad Carlos III of Madrid, Spain, where he promptly joined Deloitte’s IT risk advisory department as a Data Scientist. He was involved in big data, information retrieval, and digital transformation projects for one of the biggest bank corporations in Europe.
Due to his passion for researching, during his Master’s program at Syracuse University, he worked as a research assistant with Professor Asif Salekin at the Ubiquitous and Intelligent Sensing Laboratory Lab. Their research was focused mainly on early-stage Alzheimer’s disease detection using Deep Learning techniques in 3D brain scans. The promising results of their research awarded them with the ‘IAAI Deployed Application Award’. These experiences helped him to develop a strong set of technical skills, especially in deep learning, reinforcement learning, and sequence learning.