Your question is Owning Model Drift in Production. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
Tell me about a time you deployed a machine learning model into production and later had to detect or respond to data drift. How did you set up the deployment and monitoring process, what signals told you something was wrong, and what did you do next?