Lyft
Mid
Drive metrics, A/B tests, and executive-facing insights for Lyft's Safety & Customer Care support platform
This interview is for a Data Analytics Lead role embedded in Lyft's Safety & Customer Care (SCC) organization, focused on defining success metrics for the support platform, building dashboards, designing A/B tests, and presenting findings to senior leadership. Expect SQL/Python technical screens alongside stakeholder-management and business-translation questions, since the role explicitly requires converting unstructured business problems into clear analytical requirements with minimal oversight.
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What this interview tests
- Metrics definition and dashboarding for a support/safety platform
- A/B test design and evaluation of product/operational changes
- SQL and Python for large-scale, multi-source data synthesis
- Translating ambiguous business problems into scoped analyses
- Cross-functional partnership (Product, Engineering, Data Science, BizOps)
- Executive-level communication of KPI performance and recommendations
Common question themes
Walk through how you'd define the health metrics for a customer support platform from scratch
Design an A/B test to evaluate a new support feature or operational change — what's your success metric?
Tell me about a time you turned a vague business ask into a clear analytical framework with minimal guidance
Describe a SQL/Python analysis where you synthesized data from multiple disconnected sources
How do you diagnose a KPI regression and present it to senior leadership?
How have you built trust and driven decisions across Product, Engineering, and Business Operations as an analytics partner?
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