
Sign up to save your podcasts
Or


Hugo speakswith Katie Bauer about her time working in data science at both Twitter and Reddit. At the time of recording, Katie was a data science manager at Twitter and prior to that, a founding member of the data team at Reddit. She’s now Head of Data Science at Gloss Genius so congrats on the new job, Katie!
In this conversation, we dive into what type of challenges social media companies face that data science is equipped to solve: in doing so, we traverse
I’ve always found conversations with Katie to be a treasure trove of insights into data science and machine learning practice, along with key learnings about data science management.
In a word, Katie helps me to understand our space better. In this conversation, she told me that one important function data science can serve in any organization is creating a shared context for lots of different people in the org. We dive deep into what this actually means, how it can play out, traversing the world of dashboards, metric stores, feature stores, machine learning products, the need for top-down support, and much, much more.
By Hugo Bowne-Anderson5
1111 ratings
Hugo speakswith Katie Bauer about her time working in data science at both Twitter and Reddit. At the time of recording, Katie was a data science manager at Twitter and prior to that, a founding member of the data team at Reddit. She’s now Head of Data Science at Gloss Genius so congrats on the new job, Katie!
In this conversation, we dive into what type of challenges social media companies face that data science is equipped to solve: in doing so, we traverse
I’ve always found conversations with Katie to be a treasure trove of insights into data science and machine learning practice, along with key learnings about data science management.
In a word, Katie helps me to understand our space better. In this conversation, she told me that one important function data science can serve in any organization is creating a shared context for lots of different people in the org. We dive deep into what this actually means, how it can play out, traversing the world of dashboards, metric stores, feature stores, machine learning products, the need for top-down support, and much, much more.

476 Listeners

1,083 Listeners

434 Listeners

302 Listeners

340 Listeners

268 Listeners

210 Listeners

194 Listeners

89 Listeners

489 Listeners

133 Listeners

97 Listeners

33 Listeners

18 Listeners

52 Listeners