Your question is Feature Engineering for Supervised Models. 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're preparing data for a supervised learning problem and comparing several candidate models. Raw columns are available, but you suspect the model will perform better if the inputs better reflect the underlying patterns.
What is feature engineering, and why is it important?