A high-AUC churn model that changes no behavior is worthless. The strong answer nails the label definition, chooses classification vs survival deliberately, and is judged on retention uplift, not accuracy.
Updated Sep 2026 · Grounded in real GenAI, LLM, and AI/ML engineering interview loops and written to a senior-engineer editorial bar.
A high-AUC churn model that changes no behavior is worthless. The strong answer nails the label definition, chooses classification vs survival deliberately, and is judged on retention uplift, not accuracy.
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.
