Daniel Alvarez

Daniel Alvarez is a data science professional with a passion for using data analysis to address societal challenges and influence decision-making. He holds a Bachelor's degree in Economics and International Affairs from Brown University, a Master's degree in Public Administration with a focus on Advanced Policy and Economic Analysis from Columbia University's School of International and Public Affairs, and additional education in data science and economics from UC Berkeley and Pontifícia Universidade Católica do Rio de Janeiro. Daniel has a diverse professional background, with experience at economic litigation consulting firm Cornerstone Research, the Federal Reserve Bank of New York, and USAA, where he specialized in predictive modeling, statistical modeling, and data science using tools like SAS, R, Python, Stata, and SQL. His expertise includes government affairs, policy analysis, and financial policy compliance.

Daniel's career trajectory includes roles such as Data Scientist at the World Food Programme, Sr. Quantitative Risk Analyst at USAA, Risk Analytics Associate at the Federal Reserve Bank of New York, Bank Examiner, and Graduate Intern at the Federal Reserve Bank of New York, along with an earlier role as an Analyst at Cornerstone Research. His educational background and professional experience demonstrate a strong foundation in data science, policy analysis, and economic research, positioning him as a valuable asset in tackling complex societal problems through data-driven insights and strategic decision-making.