Uploaded November 2023 | Updated September 2026, 2 weeks ago
Pan Wu is a senior manager of data science at Meta. After finishing his PhD from Duke University, he started his career in machine learning engineering and applied science, later he focused more on product data science. Before Meta, he worked in TrueCar, Uber, and LinkedIn. Pan has a decade-long expertise in machine learning and data science. Today we’ll talk about why he moved from machine learning to product data science, projects he worked on at Uber, Linkedin, and Meta, and how he compares the culture among those companies and how he transitioned from IC to manager. If you like the show, subscribe to the channel, give me a five-star review and leave a comment. Subscribe to Daliana's newsletter on www.dalianaliu.com for more on data science and career.
Pan’s LinkedIn: linkedin.com/in/panwu/
Daliana's Twitter: twitter.com/DalianaLiu
Daliana’s LinkedIn: linkedin.com/in/dalianaliu
00:00:00 Introduction
00:01:30 Why he transitioned from MLE to product DS
00:07:38 Meta data scientists skill sets
00:15:49 When did his interest shifted from MLE to product DS
00:18:04 Is MLE more respected?
00:25:46 A/B testing deep dives in 3 steps
00:28:21 Built a tool at Linkedin
00:35:52 How to sell your project
00:41:07 Junior vs senior data scientist
00:43:24 From staff data scientist to manager
00:45:18 Explore being a manager
00:46:24 Cultures in Uber, Linkedin, TrueCar
00:52:09 Data science over the past 10 year
00:55:06 MLE vs DS fun and frustration
00:57:26 Product DS reality
00:59:10 Learning new skills
01:01:39 Mistakes he made
01:06:34 Future of data science
01:08:04 Will data scientists be replaced by AI
01:09:42 Three skills he looks for when hiring
Pan Wu is a senior manager of data science at Meta. After finishing his PhD from Duke University, he started his career in machine learning engineering and applied science, later he focused more on product data science. Before Meta, he worked in TrueCar, Uber, and LinkedIn. Pan has a decade-long expertise in machine learning and data science. Today we’ll talk about why he moved from machine learning to product data science, projects he worked on at Uber, Linkedin, and Meta, and how he compares the culture among those companies and how he transitioned from IC to manager. If you like the show, subscribe to the channel, give me a five-star review and leave a comment. Subscribe to Daliana's newsletter on www.dalianaliu.com for more on data science and career.
Pan’s LinkedIn: linkedin.com/in/panwu/
Daliana's Twitter: twitter.com/DalianaLiu
Daliana’s LinkedIn: linkedin.com/in/dalianaliu
00:00:00 Introduction
00:01:30 Why he transitioned from MLE to product DS
00:07:38 Meta data scientists skill sets
00:15:49 When did his interest shifted from MLE to product DS
00:18:04 Is MLE more respected?
00:25:46 A/B testing deep dives in 3 steps
00:28:21 Built a tool at Linkedin
00:35:52 How to sell your project
00:41:07 Junior vs senior data scientist
00:43:24 From staff data scientist to manager
00:45:18 Explore being a manager
00:46:24 Cultures in Uber, Linkedin, TrueCar
00:52:09 Data science over the past 10 year
00:55:06 MLE vs DS fun and frustration
00:57:26 Product DS reality
00:59:10 Learning new skills
01:01:39 Mistakes he made
01:06:34 Future of data science
01:08:04 Will data scientists be replaced by AI
01:09:42 Three skills he looks for when hiring
