---
esco_uri: http://data.europa.eu/esco/skill/08b04e53-ed25-41a2-9f90-0b9cd939ba3d
esco_label: "manage research data"
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
---

# manage research data — Data Scientist

For a Data Scientist, 'managing research data' isn’t just about archiving; it's deeply woven into the entire project lifecycle. Daily tasks include meticulous version control of datasets (using tools like Git & DVC), documenting data provenance – *exactly* how each feature was derived or transformed – and ensuring reproducibility. This means not only saving raw data but also the code used to clean, process, and analyze it. Think beyond simple storage; you're building a 'data lineage' that allows others (or your future self!) to understand and validate your findings.  A key part is often creating well-documented feature stores or data catalogs.

## Weitere Anreicherung

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