---
esco_uri: http://data.europa.eu/esco/skill/9a58cd26-58eb-4a1c-b1b6-64037fe9cfa1
esco_label: "think abstractly"
relation: essential
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
---

# think abstractly — Data Scientist

For a Data Scientist, 'thinking abstractly' isn’t about philosophical musings; it's the core skill enabling you to translate messy real-world problems into solvable analytical frameworks. Daily this means moving *beyond* the immediate data and understanding the underlying business problem – what are we *really* trying to predict or understand? It manifests in feature engineering (seeing beyond raw values to create meaningful indicators), model selection (choosing an algorithm not just for accuracy, but for its ability to generalize to unseen data & interpretability), and interpreting results. You're constantly building mental models of the system you’re analyzing.

## Weitere Anreicherung

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