---
esco_uri: http://data.europa.eu/esco/skill/fbafa41f-cd05-4109-a649-8b44d306d779
esco_label: "create data models"
relation: optional
onet_soc: 15-2051.00
source: model-knowledge
confidence: high
qa_count: 0
generator: gemma3:27b (prompt-designed and spot-checked by Claude)
generated: 2026-07-10
---

# create data models — Data Scientist

As a Data Scientist, 'creating data models' isn’t about drawing ER diagrams for database admins – it's about *translating business problems into structures that machine learning algorithms can understand*. Daily tasks involve taking messy, real-world data (think customer interactions, sensor readings, web logs) and defining how those pieces relate to each other *for predictive purposes*. This means going beyond just identifying entities; you’re thinking about features, transformations needed for model input, and potential biases embedded in the data structure. You'll often be building 'feature stores' – organized collections of these modeled features ready for training.

## Weitere Anreicherung

Stage-2 source for future practitioner grounding: arXiv cs.LG/stat.ML (ML preprints).
