Lyft Data Analyst Interview Guide

Lyft Data Analyst interviews described by candidates place analytical communication alongside SQL and business judgment. One candidate reported an initial screening, recruiter conversation, a two-person phone interview, a take-home, and a final loop. The phone discussion mixed behavioral and product-sense prompts, including an investigation of falling activation rates. Later conversations covered ridership, activation metrics, SQL, business cases, and explaining technical terms to non-technical stakeholders.

A separate candidate’s most demanding assignment was a dataset-based analysis presentation completed over a weekend. That candidate also described a whiteboard exercise requiring pseudocode for a complex SQL solution, plus a case discussion on problem solving, business insight, and analytical reasoning. Prepare to narrate how you structure an analysis, not merely deliver a query or chart. Practice framing a metric drop as an investigation, then state the data you would examine, the reasoning behind it, and how you would communicate the result to a business audience.

The available reports do not provide a consistent end-to-end timeline. Candidates characterize the structure as straightforward but demanding, particularly when the take-home deadline and whiteboard SQL explanation require concise, well-organized communication.