Your question is Handling Missing Data in Finance. 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 missing or corrupted data in large-scale financial datasets without introducing bias?
Address how you would distinguish missingness mechanisms, detect corruption, choose deletion or imputation methods, and validate that downstream estimates remain reliable. Explain how your approach would change for transaction, market, and customer data, and how you would monitor the process in production.