
What are The Skillsets Needed to be an Effective Data Scientist (Eugene Yan) - KNN Ep. 48
About this episode
I had the pleasure of interviewing Eugene Yan. he works at the intersection of machine learning and product to build pragmatic, customer-facing ML systems. He also writes & speaks about effective data science, data/ML systems, and career growth.
Currently, He is an Applied Scientist at Amazon shipping ML and recommends systems to help customers read more.
On his website, he shares what he’s learned on shipping ML systems, with a pragmatic and product slant. He’s written 119 posts and 215,291 words so far!
In this episode, we learn about how Eugene broke into data science from a psychology background. We also go through the challenges of breaking into the US job market. I learned quite a bit about the visa process and how different countries can have different visa quotas. Finally, we touch on the importance of end to end data science and how sharing your work can help you to make your own luck. I had a great experience getting to know Eugene better through this interview, and I hope you learn a lot from this episode!
Get every episode summarized
Each time Ken's Nearest Neighbors publishes, we email you a written briefing from the transcript — the topics, who appeared, and any specific claims, with the ad reads skipped.
Email me new episodesFree for 3 shows. No card needed.
Hosts & guests
No transcript yet
This episode has not been transcribed. Request it and it moves to the front of the queue.
More episodes
More from Ken's Nearest Neighbors

How Can Data Teams Get Out of Their Own Way (Alex Gold) - KNN Ep. 196
Ken's Nearest Neighbors

How She Went From Analytics Executive to Solopreneur (Serena Huang PhD) - KNN E...
Ken's Nearest Neighbors

The Journey of a Non-Technical Founder in a Data Company (Jake Schuster) - KNN E...
Ken's Nearest Neighbors

Inside New York's Most Exclusive Data Community (Derek Larson) - KNN Ep. 193
Ken's Nearest Neighbors