Today I had the pleasure of interviewing Eugene Yan. he works at the intersection of machine learning & 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 recommender systems to help customers read more.
On his website, he shares what he’s learnt on shipping ML systems, with a pragmatic & 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!
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