Welcome to your interview.
The question is on your right: Missing Values and Outlier Handling. 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 data for a supervised learning task and notice that some features have missing values and a few columns contain extreme observations. You want a preprocessing approach that improves model quality without distorting the underlying signal.
Explain how you handle missing values and outliers during the data preprocessing phase.