ABOUT ME

My interest in data science and economics began in high school with a deep affinity for numbers, analytical methods, and economic theory. This led me to the Barcelona School of Economics, where I completed two Master's degrees: one in Economics of Energy, Sustainability and Climate Change, and a second in Data Science for Decision Making — where I explored machine learning, deep learning, NLP, and their applications in finance.

Beyond academia, I have gained substantial professional experience across leading institutions. At the European Central Bank, I developed a full-stack web application for supervisory metadata, built automated validation pipelines for Pillar 3 compliance, and prototyped a Python AI inbox agent using a RAG pipeline. At the International Energy Agency, I migrated investment calculation models to Python, co-authored a section of the IEA's published report on electricity in the Middle East and North Africa, and built a web scraping tool for large-scale data collection. At Deloitte, I created Tableau dashboards and Python/SQL workflows for M&A due diligence analytics.