Episode 49: Computational Neuroscience, Quantitative Finance, and Churn Prediction with Carl Gold

• (1:57) Carl recalled his undergraduate experience studying Electrical Engineering at Stanford back in the early 90s.
• (3:58) Carl recalled his graduate experience pursuing Master’s degrees in Computer Science at NYU and King’s College in the late 90s. For his Master's Thesis, he investigated Support Vector Machines with a Bayesian algorithm programmed in C.
• (6:45) Carl walked over his Ph.D. work in Computation and Neural Systems at CalTech, where he did a thesis on Biophysics of Extracellular Action Potentials.
• (13:11) Carl provided brief thoughts about his experience working as a business analyst and consultant for HBO during his Ph.D. period.
• (14:55) Carl went over his rationale behind his decision to move from academic neuroscience to quantitative finance.
• (19:19) Carl discussed his proudest accomplishments and valuable lessons learned from spending seven years at Morgan Stanley Capital International and rising to a leadership role as Vice President of Risk Modeling.
• (23:17) Carl uncovered his move to San Francisco to work as a lead data scientist at Sparked back in 2014, which builds a customer success SaaS solution.
• (27:10) Adding to his move to Zuora in 2015, Carl explained how the subscription business model works in layman terms.
• (31:44) Carl unpacked the common patterns that he saw from analyzing subscriber churn for companies across industries due to his work on Zuora Analytics.
• (33:30) Carl shared the process of creating the Subscription Economy Index, Zuora’s landmark index tracking the rapid ascent of the Subscription Economy, and distilled the key trends of the 2020 edition.
• (39:59) Carl unpacked the three reasons that make churn hard to fight: (1) Churn is hard to predict, (2) Churn is harder to prevent, and (3) Churn requires a multi-team effort (Watch his talks at the 2019 Data Council San Francisco and the 2020 Subscribed Online Conference).
• (44:46) Carl shared advice for data scientists who want to collaborate more effectively with other functional departments.
• (46:30) Carl emphasized the importance of creating great customer metrics, which are ratios of basic behavioral metrics to fight churn effectively.
• (53:49) Carl went over the challenges of writing “Fighting Churn With Data,” which provides a clear overview of churn concepts, along with hands-on tricks and tips developed through years of experience analyzing customer behavior.
• (55:53) Carl reflected on how his academic background in computational neuroscience contributes to his success as a quant analyst and a data scientist.
• (59:37) Carl compared his experience living and working across Los Angeles, New York, and San Francisco.
• (01:02:04) Closing segment.

• LinkedIn
• Twitter
• GitHub
• Google Scholar
• Medium

• “Fighting Churn With Data” by Carl Gold
• Konrad Kording (Professor of Computational Neuroscience at the University of Pennsylvania)
• Kate Crawford (Distinguished Research Professor in Tech, Culture, and Society at New York University)
• Cassie Kozyrkov (Chief Decision Scientist at Google)
• "Freakonomics" by Stephen Dubner and Stephen Levitt
• Carl's other podcast appearances

Here are the discount codes that you can use to purchase "Fighting Churn with Data" with 40% off:

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About the show

Datacast features long-form, in-depth conversations with practitioners and researchers in the data community to walk through their professional journeys and unpack the lessons learned along the way. I invite guests coming from a wide range of career paths — from scientists and analysts to founders and investors — to analyze the case for using data in the real world and extract their mental models (“the WHY and the HOW”) behind their pursuits. Hopefully, these conversations can serve as valuable tools for early-stage data professionals as they navigate their own careers in the exciting data universe.

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