Problem
Scenario
You've shipped a product change and want to understand whether the movement in a key metric reflects normal recurring patterns or a true product effect. The team wants to separate expected calendar behavior from launch-driven impact so decisions are based on signal, not noise.
Question
How would you identify whether a metric change is seasonal or caused by a product launch?
What this tests
- Time-series thinking
- Causal attribution
- Metric diagnosis
- Use of leading indicators
Practicing as: Data Scientist interview at Meta LogisticsHi, I'll play your Meta Logistics interviewer for the Data Scientist role. Candidates describe these interviews as mostly positive and moderately difficult, so expect me to be friendly and conversational. Take your time with the question above and answer like we're in the room.
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