---
esco_uri: http://data.europa.eu/esco/skill/c544a9f3-5945-4b54-afed-de0697852817
esco_label: "report analysis results"
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
---

# report analysis results — Data Scientist

As a Data Scientist, 'report analysis results' isn’t just *writing* about findings; it's translating complex technical work into actionable insights for stakeholders who likely aren't data experts. Daily this means crafting clear narratives around model performance (accuracy, precision, recall), feature importance, and observed trends in the data. You'll frequently be building dashboards in tools like Tableau or Power BI *alongside* more detailed reports using Jupyter Notebooks/R Markdown – the dashboard is the 'headline', the report provides supporting evidence & methodology. Expect to present these findings verbally too, tailoring your explanation to the audience (business leaders need different details than engineering teams).

## Weitere Anreicherung

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