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Senior Data Scientist

Checked
alirezarezvani·vlatest·data·MIT

Leverages Alireza Rezvani's data science expertise to analyze complex datasets & provide actionable insights for strategic decisions.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add alirezarezvani/claude-skills --skill senior-data-scientist -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

alirezarezvani

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned alirezarezvani/claude-skills at 19392f7a08.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
19392f7a08
Manifest
engineering-team/skills/senior-data-scientist/SKILL.md
Scanned
7 files, 754 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

This skill empowers AI agents to operate with the expertise of a senior data scientist, enabling them to design complex analytical workflows and interpret advanced statistical patterns. It allows agents to move beyond basic queries to perform high-level reasoning on datasets and generate actionable insights from raw information.

When to use it

  • Analyzing large, unstructured datasets to identify hidden trends or anomalies.
  • Designing custom machine learning pipelines for specific business problems.
  • Explaining complex statistical models in clear, non-technical language to stakeholders.
  • Validating data integrity and suggesting improvements for data collection strategies.

Key capabilities

  • Advanced statistical analysis and hypothesis testing.
  • Machine learning model selection and evaluation.
  • Data visualization strategy and interpretation.
  • Experimental design and A/B testing frameworks.
  • Predictive modeling and time-series analysis.

Example prompts

  • "Act as a senior data scientist to analyze this sales CSV and identify seasonal trends that our current dashboard misses."
  • "Design an A/B testing framework for our new app feature, including sample size calculations and success metrics."
  • "Explain the implications of a high p-value in our regression model and suggest next steps for data collection."

Tips & gotchas

Ensure you provide clean, well-structured data files when requesting analysis to maximize accuracy. For complex modeling tasks, specify your preferred tools (e.g., Python/Pandas, SQL) to align with your existing tech stack.