---
esco_uri: http://data.europa.eu/esco/skill/7159e587-c7cb-4ec0-a662-03e1dee2cccb
esco_label: "research design"
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
---

# research design — Data Scientist

For a Data Scientist, 'Research Design' isn’t about academic papers – it's about framing *business problems* as answerable data questions. Daily tasks involve translating vague requests ('improve customer retention') into concrete hypotheses ('customers with X characteristic are likely to churn if Y happens'). This means defining measurable outcomes (KPIs), identifying relevant data sources, and choosing the right analytical approach *before* touching code. It's less about 'pure' research and more about applied experimental design – A/B testing is a huge part of this, as are quasi-experimental designs when true randomization isn’t possible.

## Weitere Anreicherung

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