Perfil de habilidad

Pandas / NumPy

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 with pandas DataFrame for loading, cleaning, and analyzing data. Performs basic operations: filtering, grouping, aggregation, merge/join. Uses numpy for mathematical operations and array manipulation. Builds pivot tables and descriptive statistics.

Rol	Obligatorio	Descripción
Data Scientist		Efficiently works with large datasets via pandas: chunked processing, dtype optimization, multi-index. Applies numpy vectorized operations for high-performance computing. Uses pandas profiling for automated EDA.

Rol	Obligatorio	Descripción
Data Scientist		Designs high-performance data processing pipelines with pandas/numpy. Applies advanced techniques: Cython extensions, numba JIT compilation for numpy. Optimizes memory footprint through chunked processing and memory-mapped arrays for out-of-core computing.

Rol	Obligatorio	Descripción
Data Scientist		Defines data handling standards for the data science team. Establishes shared data processing utilities and best practices. Coordinates migration from pandas to distributed frameworks (Dask, Polars, Spark) when needed.

Rol	Obligatorio	Descripción
Data Scientist		Shapes data processing stack strategy for the organization. Defines when to use pandas vs Polars vs Spark for different scales. Evaluates emerging tools and their fit for the organization's data science workflow.

Junior 1 requisitos

Data Scientist

Works with pandas DataFrame for loading, cleaning, and analyzing data. Performs basic operations: filtering, grouping, aggregation, merge/join. Uses numpy for mathematical operations and array manipulation. Builds pivot tables and descriptive statistics.

Middle 1 requisitos

Data Scientist

Efficiently works with large datasets via pandas: chunked processing, dtype optimization, multi-index. Applies numpy vectorized operations for high-performance computing. Uses pandas profiling for automated EDA.

Senior 1 requisitos

Data Scientist

Designs high-performance data processing pipelines with pandas/numpy. Applies advanced techniques: Cython extensions, numba JIT compilation for numpy. Optimizes memory footprint through chunked processing and memory-mapped arrays for out-of-core computing.

Lead / Staff 1 requisitos

Data Scientist

Defines data handling standards for the data science team. Establishes shared data processing utilities and best practices. Coordinates migration from pandas to distributed frameworks (Dask, Polars, Spark) when needed.

Principal 1 requisitos

Data Scientist

Shapes data processing stack strategy for the organization. Defines when to use pandas vs Polars vs Spark for different scales. Evaluates emerging tools and their fit for the organization's data science workflow.

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