Data Science at The New York Times
In January 2014 I began building and leading the Data Science Group within The New York Times, which develops and deploys predictive and prescriptive models and algorithms to solve business, newsroom, and strategy challenges. Building data capability while respecting existing organization, process, and technology requires understanding of all three; I'll illustrate the capabilities of the Data Science Group along with lessons learned about how to help an existing company unlock the value in its own data.
Chris Wiggins is an associate professor of applied mathematics at Columbia University and the Chief Data Scientist at The New York Times. At Columbia he is a founding member of the Department of Systems Biology, the executive committee of the Data Science Institute (http://datascience.columbia.edu/), and the Institute's education and entrepreneurship committees. He is also an affiliate of Columbia's Department of Statistics and a founding member of Columbia's Center for Computational Biology and Bioinformatics (C2B2). He is a co-founder and co-organizer of hackNY (http://hackNY.org), a nonprofit which since 2010 has organized once a semester student hackathons and the hackNY Fellows Program, a structured summer internship at NYC startups. Prior to joining the faculty at Columbia he was a Courant Instructor at NYU (1998-2001) and earned his PhD at Princeton University (1993-1998) in theoretical physics. In 2014 he was elected Fellow of the American Physical Society and is a recipient of Columbia's Avanessians Diversity Award.