Summary
Franklin Ferreira is a data scientist and PhD candidate in Physics with eight years of experience applying machine learning and computational methods to problems in credit risk, sensor analysis, and quantum-inspired simulations. He has progressed through hands-on roles at Neurotech and now Trillia, building and refining credit risk models and engineering features that drive business insights. His academic background—MSc and ongoing PhD in Physics plus an early exchange at The University of Manchester—gives him strong quantitative rigor and experience with scientific programming in Python and numerical libraries. Franklin's career began in experimental and analytical labs, where he automated electrochemical and spectroanalytical workflows, a foundation that informs his data engineering discipline today. Comfortable bridging research and production, he combines theoretical modelling instincts with practical deployment experience in industry settings. Based in Pernambuco, Brazil, he brings a curious, physics-driven approach to data science that often uncovers nonobvious variables and dynamics in real-world datasets.
8 years of coding experience