Welcome to your interview.
The question is on your right: Handling Missing and Noisy Data. Take a moment with it first.
Talk your thinking through with me if you like - when you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes). Discussion and graded submissions share your five interviewer interactions, so spend them well.
You are preparing a supervised learning dataset and notice that some fields are missing, inconsistent, or clearly noisy. You want a clean training pipeline that improves model quality without introducing leakage.
How would you handle missing or noisy data in a machine learning dataset?