Data Science at the New York Times by Chris Wiggins
For our inaugural DataEngConf 2015 we were excited to have Chris Wiggins talk about the importance of data science in a modern organization.
Chris covered the importance of bridging data science and data engineering in a company, and spoke about the interactions of their data team at The New York Times.
So what is data science? Chris explained data science as an intersection of machine learning with the decades old academic fields of statistics and computer science, and then applying these combined concepts to some particular domain of expertise.
Another way of explaining data science is a knowledge of machine learning that enables one to find the right tool for the right job, an ability to listen to people and work to figure out how to reframe their problems as machine learning tasks, and the translation of what you've learned in a way that's actionable.
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, 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, 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.