Works with
Senior Data Scientist
World-class senior data scientist skill specialising in statistical modeling, experiment design, causal inference, and predictive analytics. Covers A/B testing (sample sizing, two-proportion z-tests, Bonferroni correction), difference-in-differences, feature engineering pipelines (Scikit-learn, XGBoost), cross-validated model evaluation (AUC-ROC, AUC-PR, SHAP), and MLflow experiment tracking — using Python (NumPy, Pa
Optimized workflow
This edition turns the source methodology into a repeatable agent workflow with explicit inputs, checkpoints and deliverables.
Quality standard
- Confirm scope and missing inputs before execution
- Ground decisions in available evidence and preserve source constraints
- Return an actionable result with assumptions, risks and next steps
Agent compatibility
The same core method is packaged for Claude, Codex, GPT, Gemini, Cursor and OpenCode.
Permissions & security
Source verified · conversion tested · security signals reviewed