The Brief
Emeka is back. The P1 churn model is running and his retention team likes it. But he's noticed a gap: the model catches postpaid customers who are about to leave but misses the prepaid ones. Prepaid subscribers behave differently -- erratic top-up patterns, shorter tenure, and when they decide to leave, they just stop topping up and disappear.
He also wants to do this properly. His board approved budget for the data science work based on the first model's results. Now they want to see methodology -- requirements, evaluation plan, documented results. Not just "it works" but a structured answer to "how do you know it works?"
The dataset is the same format with three more months of data.
Your Role
You're building the next version of Emeka's churn prediction system. This time you run the full artifact creation pipeline: start with a requirements document, design your evaluation strategy before training anything, prepare the data with documented decisions, track experiments in MLflow, evaluate per segment, serve the model, and produce documentation Emeka can show his board.
You still direct Claude Code through the implementation. What changes is that the decisions are yours. P1 told you which metric to use and what threshold to hit. This time you decide.
What's New
Last time everything was provided: the algorithm, the evaluation criteria, the preprocessing instructions. You directed AI through a defined plan.
This time you make the plan. You choose the metrics. You decide how to handle encoding and imputation based on what the data looks like. You write the PRD. You design the evaluation before training starts.
The hard part is not the model. It's the decisions that come before the model -- and being able to explain why you made them.
Tools
- Python / pandas -- data loading, profiling, preprocessing
- scikit-learn -- preprocessing, training, evaluation
- MLflow -- experiment tracking (first systematic use)
- Jupyter -- notebook workflow
- FastAPI / uvicorn -- model serving
- Claude Code -- AI direction
- Git / GitHub -- version control
- curl -- API testing
Materials
You receive:
- Emeka's follow-up email describing the prepaid gap and board needs
- An updated subscriber dataset (same format, three more months)
- A data dictionary for the updated dataset
- A PRD template to structure your requirements document
- A ticket breakdown for the full project
- A project governance file (CLAUDE.md)
The brief and tickets give you structure. The metrics, preprocessing choices, and evaluation design are yours.