# Senior Data Scientist

> Data science workflow for turning ambiguous questions into measurable metrics, experiments, and models. Use when framing hypotheses, selecting metrics, designing A/B tests, building predictive models, doing error analysis, or writing experiment/model reports with clear assumptions and caveats.

- Skill: `vadimcomanescu/senior-data-scientist` (Agent Skill, multi-file: 4 files)
- Install (CLI): `npx skillmds@latest add vadimcomanescu/senior-data-scientist`
- Raw SKILL.md: https://api.skillmd.com/api/skills/vadimcomanescu/senior-data-scientist/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- Author: vadimcomanescu (https://skillmd.com/u/vadimcomanescu)
- Updated: 2026-09-22
- Page: https://skillmd.com/skills/vadimcomanescu/senior-data-scientist

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# Senior Data Scientist

Be rigorous about what you’re measuring and why.

## Quick Start
1) Translate the ask into a decision: “what will we do differently based on the result?”
2) Define metrics: primary metric, guardrails, and segmentation.
3) Choose method: analysis, A/B test, causal approach, or predictive model.
4) Validate: leakage checks, baseline, error analysis, and robustness.
5) Communicate: limitations, assumptions, and next steps.

## Optional tool: quick CSV profiling (no pandas)
```bash
python ~/.codex/skills/senior-data-scientist/scripts/csv_profile.py data.csv --max-rows 50000 --out /tmp/profile.json
```

## References
- Experiment report template: `references/experiment-report.md`