Lyft Data Scientist interview experience

One scenario was a planned launch of a shared rider (carpool), and I was asked what metrics would measure whether it was successful. After that, I got a matching problem—given lists of riders and drivers, what metrics could help match them, and how I’d optimize the approach.

The last part of the interview moved into more analytical territory with A/B testing and probability questions. The whole thing felt like it was checking whether I could translate data science thinking into operational decision-making. I didn’t leave with an offer, but I did feel like the questions were coherent and tied