---
esco_uri: http://data.europa.eu/esco/skill/4fabca9a-7435-4f33-b1da-3cdb00340fdc
esco_label: "perform scientific research"
relation: essential
onet_soc: 15-1252.00
source: model-knowledge
confidence: high
qa_count: 0
generator: gemma3:27b (prompt-designed and spot-checked by Claude)
generated: 2026-07-10
---

# perform scientific research — Software Engineer

For a Software Engineer, 'performing scientific research' isn’t about lab coats; it's about systematically investigating *technical* problems to make informed decisions. Daily this manifests as A/B testing different UI implementations to maximize user engagement (measuring click-through rates), profiling code performance to identify bottlenecks (observing execution times & memory usage), or researching the feasibility of new technologies for a project (empirical evaluation via prototypes). It's about going beyond 'this seems right' to 'we tested this, and here’s what we found'.

Typical tools include performance profilers (like VisualVM, Chrome DevTools Performance tab), statistical analysis packages (even simple spreadsheet software!), A/B testing platforms (Optimizely, LaunchDarkly), logging & monitoring systems (Splunk, ELK stack) to gather measurable data.  A key pitfall is *confirmation bias* – seeking only evidence that supports a pre-existing belief about the 'best' solution. Another is treating correlation as causation; just because two things happen together doesn’t mean one causes the other.

Good looks like: clearly defined hypotheses ('We believe changing button color will increase conversions'), rigorous data collection, statistically sound analysis (even if basic), and *documented* findings – even negative results are valuable! It also means being able to critically evaluate research papers or blog posts about new technologies, identifying potential biases or limitations in their methodology.  It's not necessarily publishing papers; it’s applying the scientific method to solve practical engineering challenges.

Finally, this competence extends to debugging. A skilled engineer doesn't just randomly try fixes; they formulate hypotheses about the root cause of a bug, design experiments (e.g., adding logging statements), and systematically test those hypotheses until the problem is isolated. This iterative process *is* scientific research applied to code.

## Weitere Anreicherung

Stage-2 source for future practitioner grounding: arXiv cs.SE (software-engineering preprints).
