This question evaluates a candidate's ability to explain production model degradation, translate technical diagnostics into non-technical language, and articulate trade-offs between user impact and delivery timelines.
You are a data scientist. A PM says:
“Your model performed great on the validation set, but after we shipped it, real-world predictions got worse. Why did this happen?”
In a 5–10 minute explanation suitable for a non-technical audience:
Assume the PM cares about user impact, timelines, and what trade-offs are involved.