Individual skill
senior-data-scientist
Use when the user asks to "design an experiment", "build a predictive model", "run A/B test analysis", "perform causal inference", "engineer features", "evaluate model performance", "set up MLOps pipeline", "analyze time series", "calculate sample size", or "deploy a model to production". Expert data science covering statistical modeling, experimentation, causal inference, feature engineering, ML deployment, and advanced analytics with Python, R, and SQL.
engineering/senior-data-scientist/SKILL.md
Source commit 2c12c7efaad13a70bdea6e205698a6c4f93a0682
What was checked
- Matches the observed repository HEAD
- Yes
- Scanner rules are current
- No
- Repository scan complete
- No
- Skill scan complete
- No
- Observed behavior
- Not checked yet
- Last checked
- Nov 4, 2026
These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.
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Repository context
- Repository stars (not skill ratings)
- 1,081
- Repository last updated
- Nov 8, 2026
- License
- NOASSERTION
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
- ai-agents Repository topic
- ai-skills Repository topic
- claude-code Repository topic
- developer-tools Repository topic
- agentic-coding Repository topic
- cursor Repository topic
- github-copilot Repository topic
- compliance-automation Repository topic
- claude-skills Repository topic
- gemini-cli Repository topic
- data-science Declared skill tag
- ml Declared skill tag
- statistics Declared skill tag
- experimentation Declared skill tag
- python Declared skill tag
- mlops Declared skill tag
- data Derived category
- engineering Derived category
- design Derived category
- devops Derived category
- testing Derived category
- data-databases Derived category
Files and excerpt
File metadata and permitted, redacted excerpts come from the recorded scan. Source links are pinned to that commit.
Browse files
SKILL.mdcore · 9,245 bytesassets/customers_sample.csvasset · 3,388 bytesassets/eval_thresholds.jsonasset · 114 bytesassets/experiment_design.jsonasset · 235 bytesassets/predictions_sample.csvasset · 1,718 bytesassets/regression_sample.csvasset · 210 bytesreferences/ds-operations.mddoc · 19,235 bytesreferences/ds-workflows.mddoc · 8,555 bytesreferences/experiment_design_frameworks.mddoc · 1,435 bytesreferences/feature_engineering_patterns.mddoc · 1,435 bytesreferences/statistical_methods_advanced.mddoc · 1,435 bytesscripts/experiment_designer.pyruns · 13,250 bytesscripts/feature_engineering_pipeline.pyruns · 14,565 bytesscripts/model_evaluation_suite.pyruns · 16,359 bytes
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