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.
Upcoming Talks
14 May 2025
Chris Wiggins, Chief Data Scientist at The New York Times, will share their application of machine learning in refining the effectiveness of their digital paywall. Learn how their paywall strategy has evolved over the past decade, where personalised meter limits are now key to enhancing both user engagement and subscription conversions. This session will offer in-depth insights into the data-driven approaches that power these optimisations, providing valuable lessons for technical professionals.
Key Outcomes Discussed:
- Enhancing user engagement and subscription conversions with personalised meter limits
- Leveraging data insights to guide both unregistered and registered users through the subscription funnel
- Balancing engagement and conversion rates through strategic trade-off management
- Mitigating demographic biases with advanced AI techniques
- Implementing historical data backtesting for continuous optimisation and improvement
14 May 2025
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