Perfil de habilidad

Time Series Analysis

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		Understands the fundamentals of Time Series Analysis. Applies basic practices in daily work. Follows recommendations from the team and documentation.

Rol	Obligatorio	Descripción
Data Scientist		Applies advanced time series methods: Prophet, SARIMA, VAR, state space models. Conducts feature engineering for temporal data: lag features, rolling statistics, Fourier features. Uses cross-validation for time series (TimeSeriesSplit).

Rol	Obligatorio	Descripción
Data Scientist		Designs production time series forecasting systems. Applies deep learning for time series: N-BEATS, Temporal Fusion Transformer, DeepAR. Implements probabilistic forecasting with quantile regression. Works with multivariate and hierarchical time series.

Rol	Obligatorio	Descripción
Data Scientist		Defines forecasting strategy for the data science team. Establishes reusable forecasting framework and evaluation standards. Coordinates forecasting platform development for business users and automated systems.

Rol	Obligatorio	Descripción
Data Scientist		Shapes forecasting and temporal analytics strategy at organizational level. Defines investments in forecasting infrastructure, evaluates foundation models for time series. Publishes methodologies and shapes thought leadership.

Junior 1 requisitos

Data Scientist

Understands the fundamentals of Time Series Analysis. Applies basic practices in daily work. Follows recommendations from the team and documentation.

Middle 1 requisitos

Data Scientist

Applies advanced time series methods: Prophet, SARIMA, VAR, state space models. Conducts feature engineering for temporal data: lag features, rolling statistics, Fourier features. Uses cross-validation for time series (TimeSeriesSplit).

Senior 1 requisitos

Data Scientist

Designs production time series forecasting systems. Applies deep learning for time series: N-BEATS, Temporal Fusion Transformer, DeepAR. Implements probabilistic forecasting with quantile regression. Works with multivariate and hierarchical time series.

Lead / Staff 1 requisitos

Data Scientist

Defines forecasting strategy for the data science team. Establishes reusable forecasting framework and evaluation standards. Coordinates forecasting platform development for business users and automated systems.

Principal 1 requisitos

Data Scientist

Shapes forecasting and temporal analytics strategy at organizational level. Defines investments in forecasting infrastructure, evaluates foundation models for time series. Publishes methodologies and shapes thought leadership.

Cargando comentarios...