---
esco_uri: http://data.europa.eu/esco/skill/696e3b5b-8b61-45af-ae4c-3ab700f197ec
esco_label: "information extraction"
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
---

# information extraction — Data Scientist

For a Data Scientist, 'Information Extraction' isn’t about *finding* data – it’s about transforming messy, real-world text into structured data usable for analysis and modeling. Daily tasks involve pulling specific facts (dates, names, quantities, relationships) from sources like customer reviews, news articles, legal documents, or even social media feeds. Think building a system to automatically identify product features mentioned in online reviews, extracting contract terms from PDFs, or categorizing support tickets based on the issue described. It's rarely about perfect accuracy initially; it’s often an iterative process of refining extraction rules and models.

## Weitere Anreicherung

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