Bernardo is a Data Scientist at the Data Science Knowledge Center, a PhD candidate in Economics, and an Instructor at Nova School of Business and Economics (Nova SBE). His is an expert on extracting insights from data to inform policy decisions. His research includes the impact of short-term rentals on housing supply, using machine learning to generate counterfactuals, and enhancing data with AI and blockchain for real estate policymaking. He has taught a wide range of graduate and undergraduate courses in data science, currently teaching Computer Programming to bachelor's students and Business Analytics to executives. Bernardo holds a dual Master's in Finance and International Management (CEMS Masters in International Management) and a Bachelor's in Business Management from Nova SBE. His professional experience spans several industries, including health, education, hospitality, energy, transportation, and telecommunications. Positions held include Senior Consultant at Deloitte, M&A Analyst at a Chinese state-owned enterprise, and Business Analyst in an SME. Most recently, during the COVID-19 pandemic, he contributed as a Data Scientist at the Directorate-General for Health (DGS). Overall, Bernardo's combined industry and academic background equips him with the skills and knowledge to assist organizations in making informed decisions and extracting insights from data.