Chris Wiggins — Chief Data Scientist at The New York Times and faculty at Columbia University — talks to our Chief Data Scientist, Jon Krohn, to provide an enthralling, witty and rich History of Data Science.
Chris:
• Is an Associate Professor of Applied Math at Columbia University.
• Has been CDS at The NY Times for nearly a decade.
• Co-authored two fascinating recently-published books: “How Data Happened: A History from the Age of Reason to the Age of Algorithms” and “Data Science in Context: Foundations, Challenges, Opportunities”
The vast majority of this episode will be accessible to anyone. There are just a couple of questions near the end that cover content on tools and programming languages that are primarily intended for hands-on practitioners.
In the episode, Chris magnificently details:
• The history of data and statistics from its infancy centuries ago to the present.
• Why it’s a problem that most data scientists have limited exposure to the humanities.
• How and when Bayesian statistics became controversial.
• What we can do to address the key issues facing data science and ML today.
• His computational biology research at Columbia.
• The tech stack used for data science at the globally revered New York Times.
The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.
