---
esco_uri: http://data.europa.eu/esco/skill/0823ccef-813f-4f22-afef-ac0d68615e8f
esco_label: "computer simulation"
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
---

# computer simulation — Data Scientist

For a Data Scientist, 'computer simulation' isn’t about building realistic video game physics; it's about *model validation* and *what-if analysis*. You'll frequently encounter situations where you build predictive models (e.g., customer churn, fraud detection) but lack real-world data to fully test edge cases or future scenarios. Simulation lets you generate synthetic datasets based on your model’s assumptions – essentially 'running the model forward' under controlled conditions. This helps identify weaknesses *before* deployment and quantify uncertainty. Think simulating thousands of potential customer behaviors to stress-test a marketing campaign prediction, or creating artificial transaction data to evaluate a new fraud rule.

## Weitere Anreicherung

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