Things to understand:
- Code: where is it, version control, what scripts are relevant to which part of the pipeline (data gathering + preprocessing, model training, prediction)
- Access provided by DD along with description of full pipeline and what each script does and produces
- Model: architecture (and alternatives considered / rejected), features being used (or explicitly not used)
- XGBoost and good understanding of features being used and why
- Documentation: where it lives
- Work in progress but I have enough informal documentation to know what's going on
- Future work: what improvements are prioritized right now
- Working with DD to identify key areas for improvement