Cassie Kozyrkov, Data Scientist at Google, recently visited the Metis Data Science Bootcamp to present to the class as part of our speaker series.
Metis instructor and Data Scientist at Datascope Analytics, Bo Peng, asked Cassie a few questions about her work and career at Google.
Bo: What is your favorite part about being a data scientist at Google?
Cassie: There is a wide variety of very interesting problems to work on, so you never get bored! Engineering teams at Google ask excellent questions and it's a lot of fun to be at the front line of satisfying that curiosity. Google is also the kind of environment where you'd expect high-impact data projects to be supplemented with some playful ones; for example, my colleagues and I have held double-blind food tasting sessions with some exotic analyses to determine the most discerning palate!
Bo: In your talk, you mention Bayesian versus Frequentist statistics. Have you picked a "side?"
Cassie: A large part of my value as a statistician is helping decision-makers fully understand the insights that data can provide into their questions. The decision maker's philosophical stance will determine what s/he is comfortable concluding from data and it's my responsibility to make this as easy as possible for him/her, which means that I find myself with some Bayesian and some Frequentist projects. That said, Bayesian thinking feels more natural to me (and, in my experience, to most students with no prior exposure to statistics).
Bo: Related to your work in data science, what has been the best advice you've received so far?
Cassie: By far the best advice was to think of the amount of time that it takes to frame an analysis in terms of months, not days. Inexperienced data scientists commit themselves to having a question like, "Which product should we prioritize?" answered by the end of the week, but there can be a tremendous amount of hidden work that needs to be completed before it's time to even begin looking at data.
Bo: How does 20% time work in practice for you? What do you work on in your 20% time?
Cassie: I have always been passionate about making statistics accessible to everyone, so it was inevitable that I'd pick a 20% project that involves teaching. I use my 20% time to develop statistics courses, hold office hours, and teach data analysis workshops.