Passionate about solving problems with data to solve real world problems of public interest.
Daniel is an innovator, advocate, technologist and creative pragmatist with an eye for problem-solving. He believes that data science can be used for social benefit to discover, diagnose and design responses to real-world problems of public interest.
Daniel has over 15 years of professional experience drawn from an array of sectors including financial risk management and analytics, humanitarian aid through cash transfers, startup ventures, enterprise software and policy implementation. His most recent experiences include serving as a pioneering data scientist at Workday and the United Nations’ World Food Programme. He serves as a mentor in data science and artificial intelligence for startups from the developing world. He holds a Master in Public Administration from Columbia University’s School of International and Public Affairs and a Master in Information and Data Science from the University of California, Berkeley. Daniel received his bachelor’s degree in Economics and International Relations from Brown University, graduating Magna Cum Laude.
Daniel hails from New York, where he lives with his wife and two young children. He enjoys traveling, biking, soccer, swimming, live music and the arts. He was born in New York City and raised in the borough of Queens in a Spanish-speaking household.