Your question is Handling Missing Data. 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).
How do you handle erroneous or missing data?
Asked in the Round 1 - Panelist 2 stage. Generic ML modeling round.
Answer this as a practical ML system design problem. Explain how you would detect data-quality issues, decide between removal, imputation, correction, or fallback behavior, and prevent bad data from affecting training and online inference. Cover validation, feature pipelines, monitoring, and recovery procedures.