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

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

0 Calificaciones
0
Episodio
164 of 197
Duración
1H 8min
Idioma
Inglés
Formato
Categoría
No ficción

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/


Escucha y lee

Descubre un mundo infinito de historias

  • Lee y escucha todo lo que quieras
  • Más de 1 millón de títulos
  • Títulos exclusivos + Storytel Originals
  • Precio regular: CLP 7,990 al mes
  • Cancela cuando quieras
Suscríbete ahora
Copy of Device Banner Block 894x1036 3
Cover for Why Data Scientists Should Break Things (Daniel Parris) - KNN Ep. 163

Otros podcasts que te pueden gustar...