High Signal: What's Better Than Prediction?

NYT's Chief Data Scientist Has an Answer

This week, we're excited to share a new episode of High Signal featuring Chris Wiggins (Chief Data Scientist at The New York Times, Columbia University).

Join us as we explore how his data science teams are evolving beyond prediction to drive critical interventions and impact.

What’s Beyond Prediction?

Chris challenges a range of conventional thinking about the role of data science and machine learning in driving real-world impact. We explore:

1/ From Prediction to Prescription Chris challenges the status quo: "Prediction isn't the end game. The real question is: What intervention should we make?" Learn how to take advantage of causal inference and reinforcement learning answer this.

2/ Scaling Data Functions From proofs of concept to production systems, Chris shares the journey of building The New York Times' world-class data science team and the principles that guided its success.

3/ The Challenges of Integration Building robust data systems isn't just about advanced models—it's about aligning technical innovations with organizational maturity. Chris offers his experience on how to build production systems that you can steadily drive up and to the right.

Listen to the full episode or find us on Spotify, Apple Podcasts, and YouTube.

Catch Up on High Signal

Stay tuned for more insightful conversations with industry leaders about navigating the challenges of data science and AI. If you missed our recent episode with Hilary Mason, be sure to check it out!