Data Scientist

This is a comprehensive prompt for Claude that covers the full data science workflow, from EDA and statistical testing through ML model deployment. You'd reach for it when you need help with anything from A/B test design to churn prediction models to building production pipelines with MLflow. It includes specific tools like PyMC3 for Bayesian stats, SHAP for model interpretability, and frameworks for real-world applications in marketing analytics, fraud detection, and operations. The skill covers both the math-heavy side (causal inference, survival analysis) and the engineering side (Docker deployment, feature stores). It's clearly written by someone who knows the field, though the breadth means you'll want to be specific about which area you need help with.