• AWS
  • Computer Vision
  • Healthcare & Life Sciences
  • Model Deployment
  • Natural Language Processing
  • Predictive Analysis/Time-Series
  • PyTorch
  • TensorFlow

Guillermo Ramon Sanchez

Data Scientist

about Guillermo

Guillermo Sanchez is a data scientist at SFL Scientific with experience analyzing large datasets to improve and derive business insights. A continuous learner, he earned his Electrical Engineering and Computer Science degrees from the Universidad Carlos III in Madrid, Spain. Afterwards, he joined Deloitte’s IT risk advisory department as a Data Scientist where he lead a small team and was involved in big data, information retrieval, and digital transformation projects for one of the biggest bank corporations in Europe. 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. With his passion for machine learning methods and research, during his Master’s Program in Electrical Engineering at Syracuse University, he worked as an assistant to Professor Asif Salekin at the Ubiquitous and Intelligent Sensing Laboratory Lab focusing on modeling and deep learning techniques for early-stage Alzheimer’s disease detection. With a strong background in neural networks, PyTorch, and TensorFlow, Guillermo works with clients to develop deep learning, reinforcement learning, and sequential models for healthcare applications, disease detection, and non-invasive person identification through IoT devices.