Skip to content

Skills suchen.../

Agent Skill Search Engine

Suche

Suche
Kategorien
Berufe

About

About
Privacy
Terms

© 2026 Skills Pool. Alle Rechte vorbehalten.

Data Science Specialist | Skills Pool

Skill-Datei

Data Science Specialist

Machine learning pipelines, data analysis, statistical modeling, and data visualization in Python. Use when asked to build an ML model, analyze a dataset, create data visualizations, write a Jupyter notebook, implement a data pipeline, tune hyperparameters, evaluate model performance, or work with pandas, scikit-learn, PyTorch, or TensorFlow.

daryllundy0 Sterne20.03.2026

Beruf
Kategorien: Datenanalyse

Skill-Inhalt

Activation criteria

User language explicitly matches trigger phrases such as build a model, analyze this dataset, machine learning.
The requested work fits this skill's lane: ML models, data analysis, Jupyter notebooks, pandas/scikit-learn/PyTorch/TensorFlow.
The task stays inside this skill's boundary and avoids adjacent areas called out as out of scope: Data infrastructure/pipelines at scale (use database-specialist or dedicated tooling).

First actions

Glob('**/*.ipynb', '**/*.csv', '**/*.parquet', '**/requirements.txt') — find notebooks, data files, dependencies
Identify: task type (classification, regression, clustering, NLP, CV, EDA), data size, and compute environment
Confirm: is this exploratory analysis, a production pipeline, or model evaluation?

Decision rules

If the request is predictive modeling: define the target variable, evaluation metric, and validation strategy before choosing a model.

Verwandte Skills

Schnellinstallation

Data Science Specialist

npx skillvault add daryllundy/daryllundy-claude-skills-library-claude-skills-data-science-specialist-skill-md

Skill herunterladen Repository öffnen

Autor: daryllundy
Sterne: 0
Aktualisiert: 20.03.2026
Beruf

Auf dieser Seite

01Activation criteria

If data quality is unclear: profile the dataset first and flag missingness, skew, leakage risk, and outliers before modeling.

If the task shifts from analysis to production service design: surface the handoff to application or platform specialists explicitly.

Output contract

For analysis: notebook or script with clear section headers; visualizations with axis labels and titles
For ML models: include train/val/test split logic, evaluation metrics appropriate to task type, and a brief interpretation of results
Always include: data shape checks, null value handling, and feature type validation

Constraints

NEVER train on test data — enforce strict train/val/test separation
Scope boundary: data infrastructure and pipeline orchestration (Airflow, dbt) belongs to database-specialist or separate tooling

Reference

references/legacy-agent.md: ML pipeline patterns, visualization templates, model evaluation frameworks, feature engineering approaches

02

First actions

03Decision rules

04Output contract

Data Scientists

Visualization Expert

Chart selection and data visualization guidance for effective data communication. Use when: creating visualizations, choosing chart types, designing dashboards, or when user mentions data visualization, charts, graphs, or needs help presenting data visually.

Shubhamsaboo106.3k

Data Analyst

SQL, pandas, and statistical analysis expertise for data exploration and insights. Use when: analyzing data, writing SQL queries, using pandas, performing statistical analysis, or when user mentions data analysis, SQL, pandas, statistics, or needs help exploring datasets.

Shubhamsaboo106.3k

Huggingface Hub

Hugging Face Hub CLI (hf) — search, download, and upload models and datasets, manage repos, query datasets with SQL, deploy inference endpoints, manage Spaces and buckets.

NousResearch98.6k

Automatisierungswerkzeuge

Multi Reviewer Patterns

Coordinate parallel code reviews across multiple quality dimensions with finding deduplication, severity calibration, and consolidated reporting. Use this skill when organizing multi-reviewer code reviews, calibrating finding severity, or consolidating review results.

CMS & Plattformen

Dbt Transformation Patterns

Master dbt (data build tool) for analytics engineering with model organization, testing, documentation, and incremental strategies. Use when building data transformations, creating data models, or implementing analytics engineering best practices.

Startup Financial Modeling

Build comprehensive 3-5 year financial models with revenue projections, cost structures, cash flow analysis, and scenario planning for early-stage startups. Use this skill when creating financial projections, calculating burn rate or runway, modeling fundraising scenarios, or preparing investor-ready financials for a seed or Series A raise.

Data Scientists