Senior Data Scientist
Skill Verifiziert AktivWorld-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.
To empower users with expert-level capabilities for designing, implementing, and analysing statistical models and experiments, translating data findings into actionable business decisions.
Funktionen
- Statistical modeling and experiment design
- Causal inference and predictive analytics
- A/B testing framework (sample sizing, analysis)
- Feature engineering pipelines
- Model training, evaluation, and MLflow tracking
Anwendungsfälle
- Designing or analyzing controlled experiments
- Building and evaluating classification or regression models
- Performing causal analysis on observational data
- Engineering features for structured tabular datasets
Nicht-Ziele
- Replacing a full-fledged data science platform
- Performing tasks outside statistical modeling and core ML workflows
- Automating data collection or cleaning beyond feature engineering needs
Documentation
- info:Configuration & parameter referenceThe provided Python scripts have argument parsers, but explicit documentation on all parameters, defaults, and precedence is missing for the arguments beyond basic input/output paths.
Execution
- info:ValidationThe Python scripts include basic argument parsing but lack explicit schema validation libraries for input arguments and structured output.
Code Execution
- info:LoggingThe Python scripts implement basic logging for initialization, processing start/end, and errors, but do not include a dedicated audit log file.
Installation
Zuerst Marketplace hinzufügen
/plugin marketplace add alirezarezvani/claude-skills/plugin install engineering-team@claude-code-skillsQualitätspunktzahl
VerifiziertVertrauenssignale
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