Drew Conway is a leading expert in the application of computational methods to social and behavioral problems at large-scale. Drew has been writing and speaking about the role of data — and the discipline of data science — in industry, government, and academia for several years. Drew has advised and consulted companies across many industries; ranging from fledgling start-ups to Fortune 100 companies, as well as academic institutions and federal agencies. Drew started his career in counter-terrorism as a computational social scientist in the U.S. intelligence community, and received his Ph.D. in political science from New York University in May, 2013.
Drew is an author of Machine Learning for Hackers, from O'Reilly Media. ML4H was written for practitioners, students, or anyone new to machine learning. The book takes a case study-based approach to introducing readers several machine learning tools. Each chapter is a self-contained exposition of a machine learning technique; including, classification, prediction, clustering, and network analysis.
Drew is a co-founder of DataKind, a non-profit organization that brings together leading data scientists with high impact social organizations through a comprehensive, collaborative approach that leads to shared insights, greater understanding, and positive action through data in the service of humanity.
Drew is a Co-chair of the DataGotham Conference. DataGotham is a celebration of the NYC data community. The annual event consists of intense discussion, networking, and sharing of wisdom from people across all industries that work with data.
Drew currently serves as the Scientist-in-Resident at IA Ventures, an investment firm supporting companies that create competitive advantage through data.
