Perfil de habilidad

Jupyter Notebooks

Esta habilidad define expectativas en roles y niveles.

Machine Learning & AI Classical Machine Learning

Roles

donde aparece esta habilidad

Niveles

ruta de crecimiento estructurada

Requisitos obligatorios

los otros 5 opcionales

Machine Learning & AI

Classical Machine Learning

22/2/2026

Selecciona tu nivel actual y compara las expectativas.

Qué se espera en cada nivel

La tabla muestra cómo crece la profundidad desde Junior hasta Principal.

Rol	Obligatorio	Descripción
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.

Rol	Obligatorio	Descripción
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.

Rol	Obligatorio	Descripción
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.

Rol	Obligatorio	Descripción
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.

Rol	Obligatorio	Descripción
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 requisitos

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 requisitos

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 requisitos

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 requisitos

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 requisitos

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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