Dan Shiebler has a pretty unambitious hobby: a full-time University of Oxford PhD 😂! Dan researches Category Theory, a math branch that categorizes items by their behavior. By day, he's Staff Machine Learning Engineer at Twitter.
In this week's SuperDataScience episode, Dan explains to me how relatively pure mathematical research translates to improving real-world ML applications.
We also discuss:
• How Twitter labels huge datasets
• How Revenue Science can boost ad performance
• What the responsibilities of a staff software engineer at a big tech company are
• What skills are sought after in data science hires at Twitter
Listening and viewing options here.
