---
esco_uri: http://data.europa.eu/esco/skill/03a74eee-2dc6-4147-8667-5cdeb65f122d
esco_label: "manage ICT data classification"
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
---

# manage ICT data classification — Data Scientist

As a Data Scientist, 'managing ICT data classification' isn’t about *creating* the overarching policy – it’s about operationalizing it within your projects. Daily, this means understanding and applying existing data sensitivity labels (e.g., Public, Internal, Confidential, Restricted) to datasets you ingest, process, and model. You'll be frequently checking data dictionaries or metadata catalogs to determine classifications *before* touching the data; blindly processing potentially sensitive information is a major risk. Tools like data lineage trackers (e.g., Apache Atlas, Collibra), cloud provider tagging systems (AWS tags, Azure labels), and even simple spreadsheet-based inventories become essential for documenting how you’ve handled classification throughout your workflow.

## Weitere Anreicherung

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