Skill-Profil

scikit-learn

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		Uses scikit-learn for the full ML cycle: preprocessing, model training, evaluation. Applies basic models: LogisticRegression, RandomForest, SVM, KMeans. Works with Pipeline, GridSearchCV, train_test_split for correct ML workflow.

Rolle	Pflicht	Beschreibung
Data Scientist		Independently solves production tasks with scikit-learn using advanced preprocessing and model selection. Applies ColumnTransformer for heterogeneous data, custom transformers. Uses RandomizedSearchCV, cross_val_predict, and calibration tools.

Rolle	Pflicht	Beschreibung
Data Scientist		Designs scalable ML solutions with scikit-learn for production. Creates custom estimators, scorers, and cross-validators. Optimizes production pipelines through partial_fit for incremental learning. Integrates scikit-learn with distributed computing.

Rolle	Pflicht	Beschreibung
Data Scientist		Defines scikit-learn usage standards for the data science team. Establishes shared preprocessing pipelines and model templates. Coordinates decision-making: when scikit-learn is sufficient vs when DL frameworks are needed.

Rolle	Pflicht	Beschreibung
Data Scientist		Shapes classical ML strategy at organizational level. Defines scikit-learn's role in the ML stack alongside deep learning frameworks. Evaluates emerging alternatives (Polars ML, cuML) and plans migration strategies.

Junior 1 Anforderungen

Data Scientist

Uses scikit-learn for the full ML cycle: preprocessing, model training, evaluation. Applies basic models: LogisticRegression, RandomForest, SVM, KMeans. Works with Pipeline, GridSearchCV, train_test_split for correct ML workflow.

Middle 1 Anforderungen

Data Scientist

Independently solves production tasks with scikit-learn using advanced preprocessing and model selection. Applies ColumnTransformer for heterogeneous data, custom transformers. Uses RandomizedSearchCV, cross_val_predict, and calibration tools.

Senior 1 Anforderungen

Data Scientist

Designs scalable ML solutions with scikit-learn for production. Creates custom estimators, scorers, and cross-validators. Optimizes production pipelines through partial_fit for incremental learning. Integrates scikit-learn with distributed computing.

Lead / Staff 1 Anforderungen

Data Scientist

Defines scikit-learn usage standards for the data science team. Establishes shared preprocessing pipelines and model templates. Coordinates decision-making: when scikit-learn is sufficient vs when DL frameworks are needed.

Principal 1 Anforderungen

Data Scientist

Shapes classical ML strategy at organizational level. Defines scikit-learn's role in the ML stack alongside deep learning frameworks. Evaluates emerging alternatives (Polars ML, cuML) and plans migration strategies.

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