Write SQL for a cohort retention analysis (what % of users return in week N after signup).
The classic product-analytics SQL question. The signal is grouping users by signup cohort, deriving each activity's period offset, and counting distinct returners per offset to build the retention triangle.
Updated Sep 2026 · Grounded in real GenAI, LLM, and AI/ML engineering interview loops and written to a senior-engineer editorial bar.
The classic product-analytics SQL question. The signal is grouping users by signup cohort, deriving each activity's period offset, and counting distinct returners per offset to build the retention triangle.
Lead with where the obvious approach breaks, because that is the judgment they are screening for — most candidates jump straight to the happy path and lose the room.
Then walk the failure back through the pipeline in order, naming the one metric the customer's exec sponsor actually cares about before you propose the fix.