Tell me about a time you resolved a significant technical disagreement within your team.
Behavioral rounds at FAANG and AI labs now include 1-2 design follow-ups. Each answer below ships with both.
The situation, your role, and the stakes, compressed.
My team was split on supervised vs unsupervised anomaly detection. The supervised camp wanted classifiers to control precision; the unsupervised camp pointed out our labeled data was scarce and biased toward recent incidents. Both were right about something. We had a fixed timeline and precision/recall targets we had to hit either way.
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Design Follow-Ups
The new behavioral roundBehavioral rounds increasingly drop into 1-2 technical follow-ups that probe whether you could actually build the system you described. These are the design questions a real interviewer would ask after this STAR answer.
Design the detection layer. What's the residual computation, what outlier detector did you pick, and how do you tune it without labels?
Calibrated thresholding with scarce, biased labels: how would you actually do this without overfitting to recent incidents?