#DataScience #MachineLearning #AI In Episode #1011, Dr. Catherine Williams, Chief Data Officer at the nonprofit Candid, joins @JonKrohnLearns to talk about how was solving black-hole equations with pen and paper before she ever wrote a line of code. She earned a PhD in math researching general relativity and black holes, did postdocs at Stanford and Columbia and then became one of the very first data scientists, joining AppNexus back in 2012, around the same time “data scientist” became a job title at all. In this episode, she traces the field’s evolution from Bayesian models to BERT to today’s LLMs, and makes a compelling case that going deep on the underlying math matters more than ever, even now that AI can do the math for you. This episode is brought to you by: • Notion: http://notion.com/superdata • Acceldata: https://www.acceldata.io • Gurobi: https://www.superdatascience.com/gurobi • Cisco: https://outshift.cisco.com/ Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information. In this episode you will learn: • (00:00:00) Introduction • (00:02:40) Catherine’s black hole and general relativity research • (00:13:18) The intellectual habits that carried from math into leadership • (00:19:04) Whether deep math still matters in the age of LLMs • (00:46:36) The BERT moment and the embeddings revolution • (00:51:12) Why frontier capability keeps getting cheaper • (10:00:39) Catherine’s leadership advice: think one level up Additional materials: https://www.superdatascience.com/1011