What languages does this skill support for data analysis?

It has deep expertise in the Python ecosystem (pandas, scikit-learn, PyTorch), R programming (tidyverse), and advanced SQL for complex data manipulation.

Does it handle experimental design and A/B testing?

Yes, it provides guidance on randomized controlled trials, power analysis, sample size determination, and causal inference to ensure results are statistically significant.

Is it suitable for business-focused analytics?

Absolutely. It includes specific frameworks for marketing analytics (CLV), financial risk modeling, and operational optimization like supply chain planning.

Can this skill help with production machine learning?

Yes, it covers the full MLOps lifecycle, including model serialization with MLflow, containerization with Docker, and real-time monitoring for model drift.

Data Scientist

Name: Data Scientist
Author: ngxtm

byngxtm

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데이터 과학 및 ML

Performs advanced statistical modeling, machine learning development, and comprehensive data analysis to extract actionable business insights.

The Data Scientist skill transforms Claude into a specialized analytics partner capable of handling the entire data lifecycle, from exploratory data analysis (EDA) and hypothesis testing to the deployment of production-ready machine learning models. It provides expert guidance on statistical methodologies, feature engineering, and predictive modeling using industry-standard tools like Python, R, and SQL, making it essential for developers and analysts looking to implement rigorous, data-driven solutions and automated insights within their applications.

주요 기능

01Data engineering and pipeline orchestration with tools like Airflow and PySpark

02Comprehensive data visualization and storytelling using Matplotlib, Seaborn, and Plotly

03Advanced statistical analysis including hypothesis testing, A/B testing, and causal inference

04Specialized domain analytics for marketing, finance, operations, and supply chain

052 GitHub stars

06End-to-end machine learning workflows from feature engineering to production deployment

사용 사례

01Designing and interpreting complex experiments with rigorous statistical validation

02Building predictive churn models and customer segmentation systems for business growth

03Developing automated demand forecasting and time-series analysis for inventory planning

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add ngxtm/devkit data-scientist

For use in Claude.ai and ChatGPT