Fernando Papi

Fernando Papi is a data scientist with extensive experience in machine learning and data analysis within the financial and sports performance sectors. At Transfero Group since October 2021, Fernando has developed and deployed machine learning algorithms for high-frequency trading, designed a data ETL pipeline, and implemented an MLOps framework, achieving a model uptime of over 99%. Prior experience at Joga involved performance tracking for football players, where Fernando created GPS analysis algorithms, integrated Python with AWS, and maintained the infrastructure for automated reporting. Additionally, Fernando's earlier roles included consulting on artificial intelligence projects at Udacity, an internship at Opel focusing on autonomous driving technologies, and research in control systems at NTNU. Fernando holds a Master’s Degree in Automation Systems Engineering with a focus on Artificial Intelligence and Blockchain, along with relevant qualifications in deep learning and control engineering.