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Daniel Alvarez

Public Policy - Data Science - Risk Analytics

Daniel Alvarez is a passionate advocate for using data science to address real-world societal challenges. With a Bachelor’s degree in Economics and International Affairs from Brown University, and a Master’s degree in Public Administration specializing in Advanced Policy and Economic Analysis from Columbia University’s School of International and Public Affairs (SIPA), Daniel has accumulated a wealth of expertise in the field of data science.

Throughout his professional journey at economic litigation consulting firm Cornerstone Research, Federal Reserve Bank of New York, and USAA, Daniel has honed his skills in predictive modeling, statistical modeling, and data science. He is proficient in tools like SAS, R, Python, Stata, and SQL. His areas of interest span across government/public affairs, policy analysis, and financial policy compliance.

Daniel’s educational background includes studying Economics at Brown University, completing a Master of Public Administration at Columbia University, and pursuing a Master in Information and Data Science focused on Data Science at UC Berkeley School of Information. He also engaged in an exchange program in Economics at Pontifícia Universidade Católica do Rio de Janeiro and attended Bronx High School of Science.

With experience as a Data Scientist at the World Food Programme, a former Senior Quantitative Risk Analyst at USAA, a Risk Analytics Associate at the Federal Reserve Bank of New York, as well as various roles at the Federal Reserve Bank of New York and Cornerstone Research, Daniel Alvarez brings a diverse perspective and a strong analytical foundation to any data-driven problem. He is driven by the prospect of using data science for social good and is keen on leveraging his expertise to drive meaningful change.

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Location

Greater New York City Area