Bruno Rizzo

Bruno Rizzo has a diverse work experience in the field of data science and quantitative analysis. Bruno started their career as a PhD Fellow at Agencia de Promoción Científica y Tecnológica, where they conducted research on quantum transport and quantum information and computation. Bruno then worked as a Teacher Assistant in Physics at Universidad de Buenos Aires.

Bruno then pursued a PhD Fellowship at CONICET, specializing in condensed matter physics and studying electric charge transfer and heat conduction in semiconductors. Bruno also explored nanoelectronics, spintronics, and many-body physics.

After completing their PhD, Bruno took on a Postdoctoral Fellowship at Universidad Federal Fluminense, focusing on the study of transport properties of topological insulators and developing numerical methods for analyzing Weyl nodes.

Following their academic research, Bruno gained industry experience as a Senior Quantitative Risk Analyst at CRISIL Global Research & Analytics, working with one of the largest banks in the United States. Bruno utilized mathematical and statistical methods to solve finance-related problems and made decisions on complex derivatives pricing and risk management.

Bruno then joined YPF SA as a Data Scientist, where they defined business strategies related to Industry 4.0, Artificial Intelligence, and Machine Learning. Bruno also managed projects in these areas.

Currently, Bruno is working at Konfído as a Lead Data Scientist, conducting research on new machine learning techniques and methodologies. Bruno explores the potential application of these techniques in solving industry problems through proofs of concept, with a focus on graph machine learning.

Bruno Rizzo earned their Master's in Physics (MSc) from the University of Buenos Aires, where they later pursued their Doctor of Philosophy in Physics (PhD) degree. Bruno completed their PhD in Physical Science at the University of Buenos Aires.