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Why Data Scientists Should Break Things (Daniel Parris) - KNN Ep. 163

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Manage episode 374406257 series 3269789
Contenu fourni par Ken Jee. Tout le contenu du podcast, y compris les épisodes, les graphiques et les descriptions de podcast, est téléchargé et fourni directement par Ken Jee ou son partenaire de plateforme de podcast. Si vous pensez que quelqu'un utilise votre œuvre protégée sans votre autorisation, vous pouvez suivre le processus décrit ici https://fr.player.fm/legal.

Today I had the pleasure of interviewing Daniel Parris. Daniel is a data scientist and data journalist with over eight years of experience. He was one of DoorDash's first data science hires, and he currently invests in early-stage data products through Dash VC. He run the newsletter called Stat Significant, which crafts data-centric essays about pop culture phenomena, and Data People, a short-form interview series with world-class data professionals. Which I was featured in recently. In this episode, Daniel explains what it was like to work at a quickly growing company with an experimental culture like doordash, what he learned from his biggest mistakes, and why he decided to pursue consulting and data journalism.
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
Daniel's Links:
- LinkedIn: https://www.linkedin.com/in/daniel-parris-8324b274/
- Email: daniel@askdatapeople.com
- Newsletter: https://substack.com/@statsignificant
- Data People: https://www.askdatapeople.com/

  continue reading

194 episodes

Artwork
iconPartager
 
Manage episode 374406257 series 3269789
Contenu fourni par Ken Jee. Tout le contenu du podcast, y compris les épisodes, les graphiques et les descriptions de podcast, est téléchargé et fourni directement par Ken Jee ou son partenaire de plateforme de podcast. Si vous pensez que quelqu'un utilise votre œuvre protégée sans votre autorisation, vous pouvez suivre le processus décrit ici https://fr.player.fm/legal.

Today I had the pleasure of interviewing Daniel Parris. Daniel is a data scientist and data journalist with over eight years of experience. He was one of DoorDash's first data science hires, and he currently invests in early-stage data products through Dash VC. He run the newsletter called Stat Significant, which crafts data-centric essays about pop culture phenomena, and Data People, a short-form interview series with world-class data professionals. Which I was featured in recently. In this episode, Daniel explains what it was like to work at a quickly growing company with an experimental culture like doordash, what he learned from his biggest mistakes, and why he decided to pursue consulting and data journalism.
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
Daniel's Links:
- LinkedIn: https://www.linkedin.com/in/daniel-parris-8324b274/
- Email: daniel@askdatapeople.com
- Newsletter: https://substack.com/@statsignificant
- Data People: https://www.askdatapeople.com/

  continue reading

194 episodes

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