
#datascience #machinelearning #ai Jeff Li tells @JonKrohnLearns what it's like to work at scale as a data scientist and a machine learning engineer at Netflix, Spotify and DoorDash, as well as how to get a foot in the door at these companies. Jeff also discusses how to run forecasts and trends, and how to read their results. Listen to hear Jeff Li discuss how Spotify became a podcast powerhouse, his startup move.ai, and the tools he uses every day. This episode is brought to you by: • Dell: http://www.dell.com/dellproaistudio • Intel: https://www.dell.com/en-us/shop/dell-laptops/scr/laptops/appref=all-intel-processors-processor-brand • Airia: https://airia.com/ • Fabi: https://www.fabi.ai/ Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information. In this episode you will learn: • (00:00:00) Introduction • (00:09:05) Forecasting in data science • (00:24:18) How to get a data science job at Netflix • (00:31:39) Jeff’s experience on launching an AI startup • (00:52:07) Jeff’s AI toolkit Additional materials: https://www.superdatascience.com/947

Attention Co-Inventor: AI's Next Leap Isn't More Data (Ep. 977 with Kyunghyun Cho)

Unmetered Intelligence is Heralding the Next Renaissance (Ep. 975 with Zack Kass)

90% of AI Intelligence is Locked Away (Here's Why) #971 with Lin Qiao

Reinforcement Learning for Agents (Ep. 963 with Amazon AGI Labs’ Antje Barth)

960: In Case You Missed It in December 2025

Should Software Companies Embrace AI or fight it? — With Asana Chief Product Officer Arnab Bose

951: Context Engineering, Multiplayer AI and Effective Search — with Dropbox’s Josh Clemm

OpenAI’s head of platform engineering on the next 12-24 months of AI | Sherwin Wu

How OpenAI Builds for 800 Million Weekly Users: Model Specialization and Fine-Tuning

952: How to Avoid Burnout and Get Promoted — with “The Fit Data Scientist” Penelope Lafeuille