Skill-Profil

Time Series Analysis

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

Rolle	Pflicht	Beschreibung
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).

Rolle	Pflicht	Beschreibung
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.

Rolle	Pflicht	Beschreibung
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.

Rolle	Pflicht	Beschreibung
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 Anforderungen

Data Scientist

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

Middle 1 Anforderungen

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 Anforderungen

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 Anforderungen

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 Anforderungen

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.

Kommentare werden geladen...