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

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

Published: Dec. 14, 2020, 2 p.m.

Show Notes

  • (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.

His Contact Info

His Recommended Resources

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

  • fcddcr-6D84
  • fcddcr-4AE7
  • fcddcr-6D9C
  • fcddcr-30BF
  • fcddcr-9705