Lyft Data Analyst Interview Guide

Candidates describe the Lyft data analyst interview as broader than a SQL screen. One senior-level candidate who received an offer began with a take-home that combined SQL coding and a case study, then spoke with the hiring manager before a final loop that included technical, stakeholder management and process improvement rounds.

The SQL detail is the most concrete. That candidate was given a Rides table (with ride_region and an is_completed flag) and a Drivers table (with home_region). They were asked for weekly completed rides in San Francisco over the last 12 weeks, then weekly distinct drivers who gave at least one ride while based in San Francisco. The second question needs a join before the filter, because driver location sits on the Drivers table.

Two other candidates, both without offers, describe a different emphasis. One was given a dataset and a weekend to build a presentation, then was asked to pseudocode a complex SQL problem on a whiteboard. The other reports a case about a drop in activation rates, questions on ridership numbers, and a prompt about explaining technical terms to non-technical stakeholders. A third report, for an Analytics Manager role, included a metrics case about a 10% rise in ticket volume.

In practice, rehearse weekly bucketing and joins, and practice structuring a metric movement by first asking where the change comes from. Also practice explaining your reasoning plainly. Reports for stakeholder and process improvement rounds are thin, so prepare for those with your own project examples.