senior-data-scientist

Editorial and source context

What this Skill does

Senior Data Scientist is a source-indexed Agent Skill for data, research & analysis work. Based on the SKILL.md description, it focuses on world-class senior data scientist skill specialising in statistical modeling, experiment design, causal…. Use the linked GitHub file to confirm scope and prerequisites before enabling it.

What the author says

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, Pandas, Scikit-learn), R, and SQL. Use when designing or analysing controlled experiments, building and evaluating classification or regression models, performing causal analysis on observational data, engineering features for structured tabular datasets, or translating statistical findings into data-driven business decisions.

Compatibility and requirements

• Use an agent runtime that supports Agent Skills and the linked SKILL.md format.
• Confirm the source repository's tools, SDKs, and platform prerequisites for ui and frontend work.

How to install or import it

• Open the linked GitHub SKILL.md and review its scope and setup instructions.
• Install or import the skill using the agent runtime's documented workflow.
• Run a small, non-sensitive test and verify the output before broader use.

Permissions and risks

• Review every command, file path, network request, dependency, and credential scope before enabling it.
• GitHub stars indicate popularity, not safety or correctness; validate the source and test with non-sensitive data.

Example workflows

• Ask an AI agent to apply Senior Data Scientist to ui and frontend work described in the source record.
• Have the agent state assumptions, required tools, and expected output before using this data, research & analysis skill.
• Compare the result with the linked GitHub SKILL.md and verify it against your project requirements.