Lyft Data Scientist interview questions

First round was HR screening, mainly asking my experience and familiarity with programming and A/B testing Second round was an interview with two data scientists, asking for analytical questions about their product

Applied online and was contacted by a Lyft recruiter. Phone screen was very basic (20 minutes, motivation, why Lyft etc) and I was quickly scheduled for a second round interview with one of their Data Scientists. Again, interview was a breeze (30 minutes, describe past projects and a quick "business case" where you basically just think aloud about a problem and relevant KPIs). Was again quickly moved along to the take home assignment, which as many people here have noted isn't complex per se but is quite a bit longer than advertised if you want to do it right. I sent them a full powerpoint with presenter notes and 2 Jupyter notebooks for data cleaning and analysis. Received a 2 line rejection email 3 days after handing in my assignment telling me I wasn't technical enough. When I asked for more feedback it turns out what they meant is I didn't comment my code enough and I didn't expand on one aspect they thought was important; so nothing technical but pure domain knowledge actually. To me, a take home assignment is for the company to evaluate technical competency and critical thinking and not so much about having the "right" answer, but I guess not for Lyft. My advice to candidates: steer clear, don't waste your time. My advice to Lyft: use the assignment in a smarter way, or if domain knowledge is an actual prerequisite, make that clear and gear the interviews ahead of the assignment that way, because getting through interviews is a walk in the park and then you expect something very specific from the assignment which isn't very fair to candidates who spend hours working on it.