Data scientist — analytics, ML and statistical modeling persona
Expert data-science persona — statistics, experimental design, causal inference, ML algorithms, feature engineering and model interpretability
- What
- Expert data-science persona — statistics, experimental design, causal inference, ML algorithms, feature engineering and model interpretability
- Cost
- Free
- Needs
- a data-science task or dataset to analyze — the skill is a persona prompt the agent adopts, not software
- Install
- Copy the installer prompt below into your Muse — your agent does the rest.
Curated by Skill Harbor — @sickn33's data scientist persona: a broad expert profile spanning statistical methodology (hypothesis testing, A/B design, causal inference, time series, Bayesian stats), ML (supervised/unsupervised, deep learning, ensembles, Optuna tuning), feature engineering and interpretability (SHAP, LIME). Honest caveats: the repo's own frontmatter marks it `risk: critical` — that is its own capability taxonomy for high-capability personas, not a malware flag; it is a persona prompt, so outputs need the usual verification — it can suggest methods confidently and still be wrong about your data. MIT licensed. Skill Harbor never reviews the code, review it yourself before use. Discovered via skills.sh.
Version:
Install
Prerequisites: a data-science task or dataset to analyze — the skill is a persona prompt the agent adopts, not software Install "Data scientist — analytics, ML and statistical modeling persona" for me. It gives my agent @sickn33's data-science expert profile: statistical methodology (hypothesis testing, A/B design, causal inference, time series, Bayesian stats), ML (supervised/unsupervised, deep learning, ensembles, Optuna tuning), feature engineering and interpretability (SHAP, LIME). Note: the repo's own frontmatter marks it "risk: critical" — its own capability taxonomy, not a malware flag. MIT-licensed. Repository: https://github.com/sickn33/agentic-awesome-skills/blob/main/plugins/agentic-awesome-skills-claude/skills/data-scientist/SKILL.md 1. Fetch the SKILL.md file (and any helper files) from the repository path into a temporary folder and summarize what it does in one or two sentences. 2. Safety check: review the SKILL.md and scripts for anything suspicious (unexpected network calls, shell commands, credential harvesting). This repo should contain zero secrets in code, credentials only via the secure vault, allowed hosts declared in the SKILL.md. Verify that holds here; STOP on any red flag and tell me. 3. Install it as a skill: copy SKILL.md and its helper files into the agent's skills directory, in a folder named "data-scientist". 4. Verify with no network calls: frontmatter valid, files in place. 5. Report what was installed, where, and what I still need to do myself (e.g. point the agent at my dataset and sanity-check its statistical claims; nothing else — it's a persona). GitHub is optional: if I have a GitHub account or the gh CLI, you may use it; otherwise public access is fine. Never require it unless it's in the prerequisites above. Rules: don't touch anything outside the temp folder and the install target. If anything looks off, stop and ask me.
Questions
How do I install a build?
Every product page includes a copy-paste install prompt. Paste it into your Muse and it sets the build up for you — no manual configuration.
Where does my money go?
Straight to the seller. Skill Harbor never processes payments: checkout happens on the seller’s own page, usually Stripe.
What does the ✓ next to a creator’s name mean?
It means we confirmed the identity of the person behind the listing. It says nothing about the code itself — always check a build before installing it.