Your question is Validate a Model for Overfitting. 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).
You've built a model that looks strong on the data you trained it on, but the team is worried it may be fitting noise instead of signal. You need to validate it in a way that gives a realistic view of how it will behave on unseen data.
How would you validate a model and avoid overfitting?