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Evan Estola - On recommendation systems going bad, hiring ML engineers, giving constructive feedback, filter bubbles and much more - #9

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Manage episode 290642244 series 2838288
Content provided by Ronak Nathani, Guang Yang, Ronak Nathani, and Guang Yang. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Ronak Nathani, Guang Yang, Ronak Nathani, and Guang Yang or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

Evan Estola (https://twitter.com/estola) is a Director of Engineering at Flatiron Health where he's leading software engineering teams focused on building Machine Learning products. Throughout this episode, Evan shares various stories when recommendation systems didn’t work as expected, like this one time when members saw mathematically worst recommendations for meetups near them. He also shares why Schenectady, NY pops up on some lists of most popular cities and the story behind the Wall Street Journal article titled 'Orbitz steers Mac users to pricier hotels'. We also discuss skills Evan looks for when hiring ML engineers, how to give constructive feedback, filter bubbles and much more.

  continue reading

51 episodes

Artwork
iconShare
 
Manage episode 290642244 series 2838288
Content provided by Ronak Nathani, Guang Yang, Ronak Nathani, and Guang Yang. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Ronak Nathani, Guang Yang, Ronak Nathani, and Guang Yang or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

Evan Estola (https://twitter.com/estola) is a Director of Engineering at Flatiron Health where he's leading software engineering teams focused on building Machine Learning products. Throughout this episode, Evan shares various stories when recommendation systems didn’t work as expected, like this one time when members saw mathematically worst recommendations for meetups near them. He also shares why Schenectady, NY pops up on some lists of most popular cities and the story behind the Wall Street Journal article titled 'Orbitz steers Mac users to pricier hotels'. We also discuss skills Evan looks for when hiring ML engineers, how to give constructive feedback, filter bubbles and much more.

  continue reading

51 episodes

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