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.
Domande di colloquio [3]
Domanda 1
Investigate a 7% monthly active riders drop and a 20% wait-time increase
Ho presentato la mia candidatura tramite un'agenzia di reclutamento personale. Ho sostenuto un colloquio presso Lyft
Colloquio
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
Ho presentato la mia candidatura online. Ho sostenuto un colloquio presso Lyft (Toronto, ON) nel mese di giu 2026
Colloquio
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.