The Cost of Things in the Medium to Long-Term

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

• the difference and similarities in companies such as Twitter and Reddit,
• the major differences in being an early member of a data team and joining an established data function at a larger organization,
• the supreme importance of robust measurement and telemetry in data science, along with
• the mixed incentives for career data scientists, such as building flashy new things instead of maintaining existing infrastructure.

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.