I applied online. The process took 4 weeks. I interviewed at Lyft in Jan 2019
Interview
The process was quick and efficient. I applied to an internship position online and heard back pretty quickly from a recruiter. Next steps were a technical phone interview and then a take home exercise to complete within 24 hours. Unfortunately I did not proceed to further steps . Technical interview was very easy and take home exam was a standard prediction problem.
Interview questions [2]
Question 1
Basic statistics and probability: Find expectations of a random variable with basic distribution. How would you construct a confidence interval? How would you estimate a probability of ordering a ride? What assumptions do you need in order to estimate this probability?
Basic optimization questions: What optimization techniques ares you familiar with and how do they basically work? How would you find the optimal price given a linear demand function? take a derivative of a quadratic function.
Tackling a case involving a significant drop in monthly active riders kicked off the technical round, which felt quite intense. Then there was a probability question about commuter ride behavior, followed by an experiment design challenge focusing on marketplace balance. The behavioral portion was equally rigorous. Overall, it took about five weeks. Funny enough, I had spent the previous weekend pouring through the case-study section on PracHub, and it really helped me feel prepared. In the end, the process was tough but rewarding, and I’m glad to say I accepted the offer.
Interview questions [3]
Question 1
Investigate a 7% monthly active riders drop and a 20% wait-time increase
I applied through a staffing agency. I interviewed at Lyft
Interview
The first round is good, but the second round they asked me something about conditional probability, and ask you to solve a real problem within some time. It made me feel nervous, with two people staring at you
I applied online. I interviewed at Lyft (Toronto, ON) in Jun 2026
Interview
They scheduled an screening interview and then scheduled for a technical data science interview mostly on experimentation and stats + prob. They sent a blog about the interview which is basically about how to answer their questions.