Skill-Profil

Jupyter Notebooks

Dieser Skill definiert Erwartungen über Rollen und Level.

Machine Learning & AI Classical Machine Learning

Rollen

wo dieser Skill vorkommt

Stufen

strukturierter Entwicklungspfad

Pflichtanforderungen

die anderen 5 optional

Machine Learning & AI

Classical Machine Learning

22.2.2026

Wählen Sie Ihr aktuelles Level und vergleichen Sie die Erwartungen.

Was wird auf jedem Level erwartet

Die Tabelle zeigt, wie die Tiefe von Junior bis Principal wächst.

Rolle	Pflicht	Beschreibung
Data Scientist		Works in Jupyter Notebook/Lab for EDA, model prototyping, and result visualization. Structures notebooks with markdown descriptions, creates reproducible experiments. Uses magic commands and extensions for productivity.

Rolle	Pflicht	Beschreibung
Data Scientist		Effectively uses JupyterLab for the full ML cycle: from EDA to model evaluation. Applies papermill for parameterized notebook runs, nbconvert for report generation. Configures kernels for various environments and projects.

Rolle	Pflicht	Beschreibung
Data Scientist		Designs notebook-based workflows for team data science collaboration. Integrates notebooks with MLflow, DVC, and CI/CD. Establishes notebook development standards: templates, code quality checks, reproducibility. Creates reusable notebook components.

Rolle	Pflicht	Beschreibung
Data Scientist		Defines notebook development infrastructure for the data science team. Coordinates JupyterHub setup, resource and access management. Establishes processes for transitioning from notebook prototypes to production code.

Rolle	Pflicht	Beschreibung
Data Scientist		Shapes interactive computing platform strategy for the organization. Defines enterprise notebook infrastructure: JupyterHub, Databricks, SageMaker notebooks. Evaluates cloud vs on-premise and security requirements for data science.

Junior 1 Anforderungen

Data Scientist

Works in Jupyter Notebook/Lab for EDA, model prototyping, and result visualization. Structures notebooks with markdown descriptions, creates reproducible experiments. Uses magic commands and extensions for productivity.

Middle 1 Anforderungen

Data Scientist

Effectively uses JupyterLab for the full ML cycle: from EDA to model evaluation. Applies papermill for parameterized notebook runs, nbconvert for report generation. Configures kernels for various environments and projects.

Senior 1 Anforderungen

Data Scientist

Designs notebook-based workflows for team data science collaboration. Integrates notebooks with MLflow, DVC, and CI/CD. Establishes notebook development standards: templates, code quality checks, reproducibility. Creates reusable notebook components.

Lead / Staff 1 Anforderungen

Data Scientist

Defines notebook development infrastructure for the data science team. Coordinates JupyterHub setup, resource and access management. Establishes processes for transitioning from notebook prototypes to production code.

Principal 1 Anforderungen

Data Scientist

Shapes interactive computing platform strategy for the organization. Defines enterprise notebook infrastructure: JupyterHub, Databricks, SageMaker notebooks. Evaluates cloud vs on-premise and security requirements for data science.

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