Ken's Nearest Neighbors  cover image

Ken's Nearest Neighbors

How a Book Landed Him His Dream Job (Tyler Richards) - KNN Ep. 169

Oct 11, 2023
01:04:59

Today I had the pleasure of bringing Tyler Richards back on the show. Last time I talked with him, he was a data scientist at Meta who had just written a book on Streamlit. Now he actually works at Streamlit and is releasing a second edition of his book. He joined Streamlit right before the were purchased by Snowflake and in this episode we talk about his experience going through an acquisition, landing a job at streamlit, and why more data scientists don't pursue entrepreneurial projects. 

Podcast Sponsors, Affiliates, and Partners:
- Pathrise - http://pathrise.com/KenJee | Career mentorship for job applicants (Free till you land a job)
- Taro - http://jointaro.com/r/kenj308 (20% discount) | Career mentorship if you already have a job 
- 365 Data Science (57% discount) - https://365datascience.pxf.io/P0jbBY | Learn data science today
- Interview Query (10% discount) - https://www.interviewquery.com/?ref=kenjee |  Interview prep questions

Tyler's Links:
Install Streamlit - https://docs.streamlit.io/library/get-started/installation
Twitter - https://twitter.com/tylerjrichards
LinkedIn - https://www.linkedin.com/in/tylerjrichards/
Website - https://www.tylerjrichards.com/
Book - https://blog.streamlit.io/streamlit-for-data-science-book/


Get the Snipd
podcast app

Unlock the knowledge in podcasts with the podcast player of the future.
App store bannerPlay store banner

AI-powered
podcast player

Listen to all your favourite podcasts with AI-powered features

Discover
highlights

Listen to the best highlights from the podcasts you love and dive into the full episode

Save any
moment

Hear something you like? Tap your headphones to save it with AI-generated key takeaways

Share
& Export

Send highlights to Twitter, WhatsApp or export them to Notion, Readwise & more

AI-powered
podcast player

Listen to all your favourite podcasts with AI-powered features

Discover
highlights

Listen to the best highlights from the podcasts you love and dive into the full episode