Your question is Feature Engineering for NLP. 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 are working on an NLP model where text features drive the final prediction. The input is messy, short, and full of domain-specific terms, so the choice of preprocessing and feature representation matters.
What are the best practices for feature engineering in natural language processing?