feat: statistician skill package v0.1.0

2026-08-14 16:46:11 +02:00
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--- a/PROVENANCE.md
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+# Data provenance — statistician
+
+Where the content of this skill package comes from, counted by
+content items (tasks, competences, tools, evidence entries, curated
+knowledge). Rendered live by Gitea:
+
+```mermaid
+%%{init: {'theme':'base','themeVariables':{'pie1':'#f9a825','pie2':'#1e88e5','pie3':'#ff355e','pie4':'#d97757','pie5':'#8e24aa','pieOuterStrokeWidth':'0px','pieSectionTextColor':'#fff'}}}%%
+pie showData
+    title Content sources — statistician
+    "ESCO (occupation & competences)" : 86
+    "O*NET (tasks & tools)" : 107
+    "Job boards (market evidence)" : 140
+    "Anthropic official Claude skills" : 6
+    "External AI skill packs (mapped)" : 113
+```
+
+| Source | Items | Share | Files |
+|---|---|---|---|
+| ESCO (occupation & competences) | 86 | 19.0 % | references/profile.md, references/skills.md |
+| O*NET (tasks & tools) | 107 | 23.7 % | references/tasks.md, references/tools.md |
+| Job boards (market evidence) | 140 | 31.0 % | references/market.md (full report) + "Market evidence" headline sections |
+| Wikipedia & AI expert curation | 0 | 0.0 % | glossary, literature, usecases, intake, quality, evals/ |
+| Anthropic official Claude skills | 6 | 1.3 % | references/ai-skills.md, section "anthropics/skills" (official Claude Code skills) |
+| External AI skill packs (mapped) | 113 | 25.0 % | references/ai-skills.md (per-source attribution inside) |
+| Stack Exchange practitioner Q&A (CC-BY-SA) | 0 | 0.0 % | references/practitioner-qa.md (per-entry attribution inside) |
+
+Licensing: O*NET (USDOL/ETA, CC BY 4.0) · ESCO (© European Union) ·
+job-ad evidence via official APIs (JSearch/Adzuna) · Wikipedia content
+paraphrased with source URLs — never copied · external AI skills are
+linked, not copied (Apache-2.0/MIT/source-available, see ai-skills.md).
--- a/SKILL.md
+++ b/SKILL.md
@@ -0,0 +1,81 @@
+---
+name: statistician
+description: "Occupational skill for the role 'statistician' (also: statistic research scientist, statistics research scientist, statistics specialist, statistical scientist, statistics scientist, statistics research analyst). Use when the user asks for typical statistician work such as: Report results of statistical analyses in peer-reviewed papers and technical manuals.; Develop software applications or programming for statistical modeling and graphic analysis.; Present statistical and nonstatistical results, using charts, bullets, and graphs, in meetings or conferences to audiences such as clients, peers, and students."
+---
+
+# Statistician
+
+Statisticians collect, tabulate, and, most importantly, analyse quantitative information coming from a varied array of fields. They interpret and analyse statistical studies on fields such as health, demographics, finance, business, etc. and advise based on patterns and drawn analysis.
+
+## Core workflow
+
+1. Report results of statistical analyses in peer-reviewed papers and technical manuals.
+2. Develop software applications or programming for statistical modeling and graphic analysis.
+3. Present statistical and nonstatistical results, using charts, bullets, and graphs, in meetings or conferences to audiences such as clients, peers, and students.
+4. Determine whether statistical methods are appropriate, based on user needs or research questions of interest.
+5. Report results of statistical analyses, including information in the form of graphs, charts, and tables.
+6. Process large amounts of data for statistical modeling and graphic analysis, using computers.
+7. Identify relationships and trends in data, as well as any factors that could affect the results of research.
+8. Analyze and interpret statistical data to identify significant differences in relationships among sources of information.
+
+## How to use this skill
+
+- Read [references/profile.md](references/profile.md) for the occupation profile and scope.
+- Consult [references/tasks.md](references/tasks.md) for the full task and activity inventory.
+- Check [references/skills.md](references/skills.md) for essential vs. optional competences.
+- Check [references/tools.md](references/tools.md) for the software commonly used in this role.
+- See [references/ai-skills.md](references/ai-skills.md) — matched external AI agent skills (per-source attribution).
+
+## Key competences (essential)
+
+- apply for research funding
+- apply research ethics and scientific integrity principles in research activities
+- apply scientific methods
+- apply statistical analysis techniques
+- communicate with a non-scientific audience
+- conduct quantitative research
+- conduct research across disciplines
+- data ethics
+- data quality assessment
+- data science
+- demonstrate disciplinary expertise
+- develop professional network with researchers and scientists
+- digital data processing
+- disseminate results to the scientific community
+- draft scientific or academic papers and technical documentation
+
+## Hot technologies
+
+- IBM SPSS Statistics
+- SAS
+- The MathWorks MATLAB
+- Apache Spark
+- Tableau
+- Apache Hadoop
+- Teradata Database
+- Amazon Redshift
+- Amazon Web Services AWS software
+- IBM DB2
+
+
+<!-- hot-tech -->
+
+## Hot technologies
+
+Top tools from 50 gated job ads (see references/market.md, as of 2026-07-20):
+
+- SAS — 28 %
+- Python — 26 %
+- SQL — 20 %
+- R programming language — 16 %
+- Microsoft Excel — 14 %
+- R language — 12 %
+- JAVA — 10 %
+- Oracle — 10 %
+- Python programming language — 10 %
+- R (programming language) — 10 %
+
+<!-- hot-tech -->
+
+---
+*Sources: ESCO v1.2.1 (http://data.europa.eu/esco/occupation/ac8b3cd1-a127-4e6a-8208-5cfcf7111955), O*NET 30.3 (15-2041.00). See manifest.json for licensing/attribution.*
--- a/manifest.json
+++ b/manifest.json
@@ -0,0 +1,148 @@
+{
+  "name": "statistician",
+  "title": "statistician",
+  "version": "0.1.0",
+  "layer": "core",
+  "language": "en",
+  "generated": "2026-07-07",
+  "ids": {
+    "esco_uri": "http://data.europa.eu/esco/occupation/ac8b3cd1-a127-4e6a-8208-5cfcf7111955",
+    "esco_code": "2120.6",
+    "isco_group": "2120",
+    "onet_soc": "15-2041.00",
+    "crosswalk_match": "exactMatch"
+  },
+  "sources": [
+    {
+      "name": "ESCO",
+      "version": "1.2.1",
+      "url": "https://esco.ec.europa.eu/"
+    },
+    {
+      "name": "O*NET",
+      "version": "30.3",
+      "url": "https://www.onetcenter.org/",
+      "license": "CC BY 4.0"
+    }
+  ],
+  "attribution": "This package includes information from the O*NET Database (v30.3) by the U.S. Department of Labor, Employment and Training Administration (USDOL/ETA), CC BY 4.0. skillfactor is not endorsed by USDOL/ETA. ESCO data (v1.2.1) (c) European Union, used per the ESCO download conditions: https://esco.ec.europa.eu/en/use-esco/download",
+  "counts": {
+    "tasks": 19,
+    "dwas": 17,
+    "skills_essential": 50,
+    "skills_optional": 35,
+    "software": 70
+  },
+  "enrichment_ai_skills": {
+    "generated": "2026-07-14",
+    "method": "deterministic mapping (ISCO prefix + title/competence keywords)",
+    "sources": {
+      "anthropics/skills": {
+        "repo": "https://github.com/anthropics/skills",
+        "commit": "f6656c1",
+        "license": "Apache-2.0; the document skills (docx/pdf/pptx/xlsx) are source-available \u2014 see the LICENSE.txt in the upstream skill folder",
+        "skills": 3
+      },
+      "NVIDIA/skills": {
+        "repo": "https://github.com/NVIDIA/skills",
+        "commit": "153b14b",
+        "license": "CC-BY-4.0 (skills/docs), Apache-2.0 (code)",
+        "skills": 12
+      },
+      "google/skills": {
+        "repo": "https://github.com/google/skills",
+        "commit": "b15f327",
+        "license": "Apache-2.0",
+        "skills": 12
+      },
+      "phuryn/pm-skills": {
+        "repo": "https://github.com/phuryn/pm-skills",
+        "commit": "18468a9",
+        "license": "MIT",
+        "skills": 9
+      },
+      "davila7/claude-code-templates": {
+        "repo": "https://github.com/davila7/claude-code-templates",
+        "commit": "fa79251",
+        "license": "MIT",
+        "skills": 8
+      },
+      "foryourhealth111-pixel/Vibe-Skills": {
+        "repo": "https://github.com/foryourhealth111-pixel/Vibe-Skills",
+        "commit": "34429a8",
+        "license": "Apache-2.0",
+        "skills": 8
+      },
+      "K-Dense-AI/claude-scientific-skills": {
+        "repo": "https://github.com/K-Dense-AI/claude-scientific-skills",
+        "commit": "4d97e29",
+        "license": "MIT",
+        "skills": 8
+      },
+      "K-Dense-AI/scientific-agent-skills": {
+        "repo": "https://github.com/K-Dense-AI/scientific-agent-skills",
+        "commit": "4d97e29",
+        "license": "MIT",
+        "skills": 8
+      },
+      "brycewang-stanford/Auto-Empirical-Research-Skills": {
+        "repo": "https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills",
+        "commit": "85bf545",
+        "license": "CC-BY-4.0",
+        "skills": 8
+      },
+      "a5c-ai/babysitter": {
+        "repo": "https://github.com/a5c-ai/babysitter",
+        "commit": "44a5d58b",
+        "license": "MIT",
+        "skills": 1
+      },
+      "FlorianBruniaux/claude-code-ultimate-guide": {
+        "repo": "https://github.com/FlorianBruniaux/claude-code-ultimate-guide",
+        "commit": "5395214",
+        "license": "custom (see upstream LICENSE)",
+        "skills": 1
+      },
+      "ferdinandobons/startup-skill": {
+        "repo": "https://github.com/ferdinandobons/startup-skill",
+        "commit": "a5f97c3",
+        "license": "MIT",
+        "skills": 1
+      },
+      "fcakyon/claude-codex-settings": {
+        "repo": "https://github.com/fcakyon/claude-codex-settings",
+        "commit": "44b7c00",
+        "license": "Apache-2.0",
+        "skills": 1
+      }
+    },
+    "total_skills": 80,
+    "tiers": {
+      "core": 57,
+      "adjacent": 23
+    }
+  },
+  "provenance": {
+    "items": {
+      "esco": 86,
+      "onet": 107,
+      "jobads": 140,
+      "wiki_ai": 0,
+      "anthropic": 6,
+      "ai_skills": 113,
+      "stackx": 0
+    },
+    "share_percent": {
+      "esco": 19.0,
+      "onet": 23.7,
+      "jobads": 31.0,
+      "wiki_ai": 0.0,
+      "anthropic": 1.3,
+      "ai_skills": 25.0,
+      "stackx": 0.0
+    },
+    "method": "content items per source category"
+  },
+  "collar": "white",
+  "computer_work": true
+}
--- a/references/ai-skills.md
+++ b/references/ai-skills.md
@@ -0,0 +1,202 @@
+# External AI agent skills — statistician
+
+Proven, publicly available AI agent skills mapped to this occupation.
+Nothing is copied from the sources: every entry is a name, a one-line
+summary and a link to the upstream skill package. Each section names
+its source repository, commit, license and retrieval date.
+
+**Tiers:** `core` = the skill directly exercises a top market hard
+skill, tool or method (from gated job-ad evidence) or an essential
+ESCO competence of this occupation; `adjacent` =
+plausibly useful, secondary. Entries are capped at 12 per source
+and 80 in total per occupation (core first,
+strongest matches survive); everything beyond the caps is excluded
+and logged in the pipeline audit trail, not in this package.
+
+_Matched deterministically (ISCO group + title/competence keywords,
+tiered against market evidence + ESCO essentials) by
+`pipeline/p5_enrich_ai_skills.py` on 2026-07-14._
+
+## Source: anthropics/skills
+
+- Repository: [https://github.com/anthropics/skills](https://github.com/anthropics/skills) (commit `f6656c1`, retrieved 2026-07-14)
+- License: Apache-2.0; the document skills (docx/pdf/pptx/xlsx) are source-available — see the LICENSE.txt in the upstream skill folder
+
+| Skill | Tier | What it adds | Upstream |
+|---|---|---|---|
+| `xlsx` | adjacent | Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .xltx, .csv, or .tsv file (e.g., adding columns, computing formulas, … | [source](https://github.com/anthropics/skills/tree/main/skills/xlsx) |
+| `docx` | adjacent | Use this skill whenever the user wants to create, read, edit, or manipulate Word documents (.docx files) or Word templates (.dotx files). Triggers include: any mention of 'Word doc', 'word document', '.docx', '.dotx', or requests to … | [source](https://github.com/anthropics/skills/tree/main/skills/docx) |
+| `pdf` | adjacent | Use this skill whenever the user wants to do anything with PDF files. This includes reading or extracting text/tables from PDFs, combining or merging multiple PDFs into one, splitting PDFs apart, rotating pages, adding watermarks, creating … | [source](https://github.com/anthropics/skills/tree/main/skills/pdf) |
+
+## Source: a5c-ai/babysitter
+
+- Repository: [https://github.com/a5c-ai/babysitter](https://github.com/a5c-ai/babysitter) (commit `44a5d58b`, retrieved 2026-07-14)
+- License: MIT
+
+| Skill | Tier | What it adds | Upstream |
+|---|---|---|---|
+| `quantitative-methods` | core | Design and execute statistical analyses including regression modeling, hypothesis testing, power analysis, and robustness checks using R, Stata, SPSS, or Python | [source](https://github.com/a5c-ai/babysitter/tree/44a5d58b/library/specializations/domains/social-sciences-humanities/social-sciences/skills/quantitative-methods) |
+
+## Source: brycewang-stanford/Auto-Empirical-Research-Skills
+
+- Repository: [https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills](https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills) (commit `85bf545`, retrieved 2026-07-14)
+- License: CC-BY-4.0
+
+| Skill | Tier | What it adds | Upstream |
+|---|---|---|---|
+| `methodology-skills` | core | 13 research methodology skills. Trigger: study design, methodology selection, scientific reasoning, mentoring. Design: rigorous methods frameworks covering qualitative, quantitative, and mixed approaches. | [source](https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills/tree/85bf545/skills/43-wentorai-research-plugins/skills/research/methodology) |
+| `econ-audit` | core | Audit economic analysis outputs (fiscal briefings, macro briefings, market research, longlists, and other quantitative economic documents) against methodology standards, academic literature, and common errors. Runs structured checks across … | [source](https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills/tree/85bf545/skills/58-charlescoverdale-econstack/econ-audit) |
+| `psychology-research-guide` | core | Psychological research methods, experimental design, and analysis | [source](https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills/tree/85bf545/skills/43-wentorai-research-plugins/skills/domains/social-science/psychology-research-guide) |
+| `academic-baseline` | core | Use when working on any empirical academic research context — paper writing, data analysis, literature review, or any task involving citations, results, or publication artifacts. Establishes non-negotiable principles that govern all other … | [source](https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills/tree/85bf545/skills/60-regisely-superpapers/skills/academic-baseline) |
+| `climate-science-guide` | core | Climate data analysis, modeling workflows, and carbon neutrality research met... | [source](https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills/tree/85bf545/skills/43-wentorai-research-plugins/skills/domains/geoscience/climate-science-guide) |
+| `law-skills` | core | 9 legal research skills. Trigger: legal research, case law analysis, regulatory compliance. Design: legal databases, citation networks, and judicial analytics tools. | [source](https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills/tree/85bf545/skills/43-wentorai-research-plugins/skills/domains/law) |
+| `linear-algebra-applications` | core | Apply linear algebra concepts to research computing and data analysis | [source](https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills/tree/85bf545/skills/43-wentorai-research-plugins/skills/domains/math/linear-algebra-applications) |
+| `results-analysis` | core | This skill should be used when the user asks to "analyze experimental results", "run strict statistical analysis", "compare model performance", "generate scientific figures", "check significance", "do ablation analysis", or mentions … | [source](https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills/tree/85bf545/skills/33-Galaxy-Dawn-claude-scholar/skills/results-analysis) |
+
+## Source: davila7/claude-code-templates
+
+- Repository: [https://github.com/davila7/claude-code-templates](https://github.com/davila7/claude-code-templates) (commit `fa79251`, retrieved 2026-07-14)
+- License: MIT
+
+| Skill | Tier | What it adds | Upstream |
+|---|---|---|---|
+| `scientific-critical-thinking` | core | Evaluate research rigor. Assess methodology, experimental design, statistical validity, biases, confounding, evidence quality (GRADE, Cochrane ROB), for critical analysis of scientific claims. | [source](https://github.com/davila7/claude-code-templates/tree/fa79251/cli-tool/components/skills/scientific/scientific-critical-thinking) |
+| `denario` | core | Multiagent AI system for scientific research assistance that automates research workflows from data analysis to publication. This skill should be used when generating research ideas from datasets, developing research methodologies, … | [source](https://github.com/davila7/claude-code-templates/tree/fa79251/cli-tool/components/skills/scientific/denario) |
+| `latex-posters` | core | Create professional research posters in LaTeX using beamerposter, tikzposter, or baposter. Support for conference presentations, academic posters, and scientific communication. Includes layout design, color schemes, multi-column formats, … | [source](https://github.com/davila7/claude-code-templates/tree/fa79251/cli-tool/components/skills/scientific/latex-posters) |
+| `statistical-analysis` | core | Statistical analysis toolkit. Hypothesis tests (t-test, ANOVA, chi-square), regression, correlation, Bayesian stats, power analysis, assumption checks, APA reporting, for academic research. | [source](https://github.com/davila7/claude-code-templates/tree/fa79251/cli-tool/components/skills/scientific/statistical-analysis) |
+| `venue-templates` | core | Access comprehensive LaTeX templates, formatting requirements, and submission guidelines for major scientific publication venues (Nature, Science, PLOS, IEEE, ACM), academic conferences (NeurIPS, ICML, CVPR, CHI), research posters, and … | [source](https://github.com/davila7/claude-code-templates/tree/fa79251/cli-tool/components/skills/scientific/venue-templates) |
+| `scientific-slides` | core | Build slide decks and presentations for research talks. Use this for making PowerPoint slides, conference presentations, seminar talks, research presentations, thesis defense slides, or any scientific talk. Provides slide structure, design … | [source](https://github.com/davila7/claude-code-templates/tree/fa79251/cli-tool/components/skills/scientific/scientific-slides) |
+| `research-engineer` | core | An uncompromising Academic Research Engineer. Operates with absolute scientific rigor, objective criticism, and zero flair. Focuses on theoretical correctness, formal verification, and optimal implementation across any required technology. | [source](https://github.com/davila7/claude-code-templates/tree/fa79251/cli-tool/components/skills/ai-research/research-engineer) |
+| `market-research-reports` | core | Generate comprehensive market research reports (50+ pages) in the style of top consulting firms (McKinsey, BCG, Gartner). Features professional LaTeX formatting, extensive visual generation with scientific-schematics and generate-image, … | [source](https://github.com/davila7/claude-code-templates/tree/fa79251/cli-tool/components/skills/scientific/market-research-reports) |
+
+## Source: fcakyon/claude-codex-settings
+
+- Repository: [https://github.com/fcakyon/claude-codex-settings](https://github.com/fcakyon/claude-codex-settings) (commit `44b7c00`, retrieved 2026-07-14)
+- License: Apache-2.0
+
+| Skill | Tier | What it adds | Upstream |
+|---|---|---|---|
+| `paper-search-usage` | core | This skill should be used when user asks to "search for papers", "find research papers", "search arXiv", "search PubMed", "find academic papers", "search IEEE", "search Scopus", or "look up scientific literature". | [source](https://github.com/fcakyon/claude-codex-settings/tree/44b7c00/plugins/paper-search-tools/skills/paper-search-usage) |
+
+## Source: ferdinandobons/startup-skill
+
+- Repository: [https://github.com/ferdinandobons/startup-skill](https://github.com/ferdinandobons/startup-skill) (commit `a5f97c3`, retrieved 2026-07-14)
+- License: MIT
+
+| Skill | Tier | What it adds | Upstream |
+|---|---|---|---|
+| `startup-design` | core | Design, validate, and plan a startup from scratch. Covers market research, competitive analysis, business model, brand identity, product definition, financial projections, and validation experiments. Trigger when the user has a startup … | [source](https://github.com/ferdinandobons/startup-skill/tree/a5f97c3/startup-design) |
+
+## Source: FlorianBruniaux/claude-code-ultimate-guide
+
+- Repository: [https://github.com/FlorianBruniaux/claude-code-ultimate-guide](https://github.com/FlorianBruniaux/claude-code-ultimate-guide) (commit `5395214`, retrieved 2026-07-14)
+- License: custom (see upstream LICENSE)
+
+| Skill | Tier | What it adds | Upstream |
+|---|---|---|---|
+| `plan-pipeline-start` | core | 5-phase planning: PRD analysis, design review, technical decisions, dynamic research team, metrics. Produces a complete implementation plan + ADRs before any code is written. | [source](https://github.com/FlorianBruniaux/claude-code-ultimate-guide/tree/5395214/examples/skills/plan-pipeline/start) |
+
+## Source: foryourhealth111-pixel/Vibe-Skills
+
+- Repository: [https://github.com/foryourhealth111-pixel/Vibe-Skills](https://github.com/foryourhealth111-pixel/Vibe-Skills) (commit `34429a8`, retrieved 2026-07-14)
+- License: Apache-2.0
+
+| Skill | Tier | What it adds | Upstream |
+|---|---|---|---|
+| `denario` | core | Multiagent AI system for scientific research assistance that automates research workflows from data analysis to publication. This skill should be used when generating research ideas from datasets, developing research methodologies, … | [source](https://github.com/foryourhealth111-pixel/Vibe-Skills/tree/34429a8/bundled/skills/denario) |
+| `statistical-analysis` | core | Statistical analysis toolkit. Hypothesis tests (t-test, ANOVA, chi-square), regression, correlation, Bayesian stats, power analysis, assumption checks, APA reporting, for academic research. | [source](https://github.com/foryourhealth111-pixel/Vibe-Skills/tree/34429a8/bundled/skills/statistical-analysis) |
+| `scholar-evaluation` | core | Systematically evaluate scholarly work using the ScholarEval framework, providing structured assessment across research quality dimensions including problem formulation, methodology, analysis, and writing with quantitative scoring and … | [source](https://github.com/foryourhealth111-pixel/Vibe-Skills/tree/34429a8/bundled/skills/scholar-evaluation) |
+| `scientific-slides` | core | Build slide decks and presentations for research talks. Use this for making PowerPoint slides, conference presentations, seminar talks, research presentations, thesis defense slides, or any scientific talk. Provides slide structure, design … | [source](https://github.com/foryourhealth111-pixel/Vibe-Skills/tree/34429a8/bundled/skills/scientific-slides) |
+| `scientific-brainstorming` | core | Open-ended scientific ideation partner. Use for research gaps, mechanism exploration, interdisciplinary connections, assumptions, possible research directions, and lightweight literature matrix or A+B paper-combination idea mapping. For … | [source](https://github.com/foryourhealth111-pixel/Vibe-Skills/tree/34429a8/bundled/skills/scientific-brainstorming) |
+| `scientific-reporting` | core | Write research/technical reports with strong structure + figure standards. Supports Markdown/HTML/PDF outputs (Quarto optional), executive summary, methods, results, discussion, and reproducibility appendix. | [source](https://github.com/foryourhealth111-pixel/Vibe-Skills/tree/34429a8/bundled/skills/scientific-reporting) |
+| `slides-as-code` | core | Build research slides with text-first source (Slidev/Marp/Reveal/Quarto) and reproducible export (PDF). Includes structure, figure reuse rules, and quality checklist for top-tier scientific presentations. | [source](https://github.com/foryourhealth111-pixel/Vibe-Skills/tree/34429a8/bundled/skills/slides-as-code) |
+| `geomaster` | core | Comprehensive geospatial science skill covering remote sensing, GIS, spatial analysis, machine learning for earth observation, and 30+ scientific domains. Supports satellite imagery processing (Sentinel, Landsat, MODIS, SAR, … | [source](https://github.com/foryourhealth111-pixel/Vibe-Skills/tree/34429a8/bundled/skills/geomaster) |
+
+## Source: K-Dense-AI/claude-scientific-skills
+
+- Repository: [https://github.com/K-Dense-AI/claude-scientific-skills](https://github.com/K-Dense-AI/claude-scientific-skills) (commit `4d97e29`, retrieved 2026-07-14)
+- License: MIT
+
+| Skill | Tier | What it adds | Upstream |
+|---|---|---|---|
+| `latex-posters` | core | Create professional research posters in LaTeX using beamerposter, tikzposter, or baposter. Support for conference presentations, academic posters, and scientific communication. Includes layout design, color schemes, multi-column formats, … | [source](https://github.com/K-Dense-AI/claude-scientific-skills/tree/4d97e29/skills/latex-posters) |
+| `scholar-evaluation` | core | Systematically evaluate scholarly work using the ScholarEval framework, providing structured assessment across research quality dimensions including problem formulation, methodology, analysis, and writing with quantitative scoring and … | [source](https://github.com/K-Dense-AI/claude-scientific-skills/tree/4d97e29/skills/scholar-evaluation) |
+| `statistical-analysis` | core | Guided statistical analysis for research data - test selection, assumption checking, effect sizes, power analysis, Bayesian alternatives, and APA-formatted reporting. Use whenever a user wants to compare groups, test a hypothesis, analyze … | [source](https://github.com/K-Dense-AI/claude-scientific-skills/tree/4d97e29/skills/statistical-analysis) |
+| `venue-templates` | core | Access comprehensive LaTeX templates, formatting requirements, and submission guidelines for major scientific publication venues (Nature, Science, PLOS, IEEE, ACM), academic conferences (NeurIPS, ICML, CVPR, CHI), research posters, and … | [source](https://github.com/K-Dense-AI/claude-scientific-skills/tree/4d97e29/skills/venue-templates) |
+| `scientific-slides` | core | Build slide decks and presentations for research talks. Use this for making PowerPoint slides, conference presentations, seminar talks, research presentations, thesis defense slides, or any scientific talk. Provides slide structure, design … | [source](https://github.com/K-Dense-AI/claude-scientific-skills/tree/4d97e29/skills/scientific-slides) |
+| `geomaster` | core | Comprehensive geospatial science skill covering remote sensing, GIS, spatial analysis, machine learning for earth observation, and 30+ scientific domains. Supports satellite imagery processing (Sentinel, Landsat, MODIS, SAR, … | [source](https://github.com/K-Dense-AI/claude-scientific-skills/tree/4d97e29/skills/geomaster) |
+| `market-research-reports` | core | Generate comprehensive market research reports (50+ pages) in the style of top consulting firms (McKinsey, BCG, Gartner). Features professional LaTeX formatting, extensive visual generation with scientific-schematics and generate-image, … | [source](https://github.com/K-Dense-AI/claude-scientific-skills/tree/4d97e29/skills/market-research-reports) |
+| `research-lookup` | core | Look up current research and scientific information across three backends: fast web search via parallel-cli (default), the Parallel Chat API for deep multi-source synthesis, and Perplexity sonar-pro-search for scholarly paper searches. … | [source](https://github.com/K-Dense-AI/claude-scientific-skills/tree/4d97e29/skills/research-lookup) |
+
+## Source: K-Dense-AI/scientific-agent-skills
+
+- Repository: [https://github.com/K-Dense-AI/scientific-agent-skills](https://github.com/K-Dense-AI/scientific-agent-skills) (commit `4d97e29`, retrieved 2026-07-14)
+- License: MIT
+
+| Skill | Tier | What it adds | Upstream |
+|---|---|---|---|
+| `latex-posters` | core | Create professional research posters in LaTeX using beamerposter, tikzposter, or baposter. Support for conference presentations, academic posters, and scientific communication. Includes layout design, color schemes, multi-column formats, … | [source](https://github.com/K-Dense-AI/scientific-agent-skills/tree/4d97e29/skills/latex-posters) |
+| `scholar-evaluation` | core | Systematically evaluate scholarly work using the ScholarEval framework, providing structured assessment across research quality dimensions including problem formulation, methodology, analysis, and writing with quantitative scoring and … | [source](https://github.com/K-Dense-AI/scientific-agent-skills/tree/4d97e29/skills/scholar-evaluation) |
+| `statistical-analysis` | core | Guided statistical analysis for research data - test selection, assumption checking, effect sizes, power analysis, Bayesian alternatives, and APA-formatted reporting. Use whenever a user wants to compare groups, test a hypothesis, analyze … | [source](https://github.com/K-Dense-AI/scientific-agent-skills/tree/4d97e29/skills/statistical-analysis) |
+| `venue-templates` | core | Access comprehensive LaTeX templates, formatting requirements, and submission guidelines for major scientific publication venues (Nature, Science, PLOS, IEEE, ACM), academic conferences (NeurIPS, ICML, CVPR, CHI), research posters, and … | [source](https://github.com/K-Dense-AI/scientific-agent-skills/tree/4d97e29/skills/venue-templates) |
+| `scientific-slides` | core | Build slide decks and presentations for research talks. Use this for making PowerPoint slides, conference presentations, seminar talks, research presentations, thesis defense slides, or any scientific talk. Provides slide structure, design … | [source](https://github.com/K-Dense-AI/scientific-agent-skills/tree/4d97e29/skills/scientific-slides) |
+| `geomaster` | core | Comprehensive geospatial science skill covering remote sensing, GIS, spatial analysis, machine learning for earth observation, and 30+ scientific domains. Supports satellite imagery processing (Sentinel, Landsat, MODIS, SAR, … | [source](https://github.com/K-Dense-AI/scientific-agent-skills/tree/4d97e29/skills/geomaster) |
+| `market-research-reports` | core | Generate comprehensive market research reports (50+ pages) in the style of top consulting firms (McKinsey, BCG, Gartner). Features professional LaTeX formatting, extensive visual generation with scientific-schematics and generate-image, … | [source](https://github.com/K-Dense-AI/scientific-agent-skills/tree/4d97e29/skills/market-research-reports) |
+| `research-lookup` | core | Look up current research and scientific information across three backends: fast web search via parallel-cli (default), the Parallel Chat API for deep multi-source synthesis, and Perplexity sonar-pro-search for scholarly paper searches. … | [source](https://github.com/K-Dense-AI/scientific-agent-skills/tree/4d97e29/skills/research-lookup) |
+
+## Source: google/skills
+
+- Repository: [https://github.com/google/skills](https://github.com/google/skills) (commit `b15f327`, retrieved 2026-07-14)
+- License: Apache-2.0
+
+| Skill | Tier | What it adds | Upstream |
+|---|---|---|---|
+| `bigquery-basics` | core | Manages datasets, tables, and jobs in BigQuery. Use when you need to interact with BigQuery, run SQL queries, manage BigQuery resources (datasets, tables, views), or perform basic data ingestion and analysis. | [source](https://github.com/google/skills/tree/b15f327/skills/cloud/bigquery-basics) |
+| `bigquery-ai-ml` | core | Leverages BigQuery's built-in machine learning and GenAI capabilities for advanced data analytics. Use when you need to write SQL queries that perform time-series forecasting, detect outliers, find key drivers, or leverage generative AI … | [source](https://github.com/google/skills/tree/b15f327/skills/cloud/bigquery-ai-ml) |
+| `datalineage-bigquery-asset-impact-analysis` | core | Analyzes the downstream impact (blast radius) when a BigQuery table or view is broken, stale, or modified. Identifies all downstream tables, dashboards, and processes that will be affected. Use when: - Performing a blast radius or impact … | [source](https://github.com/google/skills/tree/b15f327/skills/cloud/datalineage-bigquery-asset-impact-analysis) |
+| `bigtable-basics` | core | Assists in provisioning instances/tables, designing performant schemas, and querying data in Bigtable. Use when designing Bigtable row keys, configuring column families, writing SQL queries or client library code (Java, Go, Python) for … | [source](https://github.com/google/skills/tree/b15f327/skills/cloud/bigtable-basics) |
+| `cloud-sql-basics` | core | This file generates or explains Cloud SQL resources. Use this file when the user asks to create a Cloud SQL instance or database for MySQL, PostgreSQL, or SQL Server. Cloud SQL manages third-party MySQL, PostgreSQL, and SQL Server … | [source](https://github.com/google/skills/tree/b15f327/skills/cloud/cloud-sql-basics) |
+| `gke-observability` | core | Configures GKE observability, including Cloud Logging, Cloud Monitoring, and managed Prometheus. Use when configuring GKE monitoring, setting up GKE logging, or configuring Prometheus metrics collection. Don't use to configure local … | [source](https://github.com/google/skills/tree/b15f327/skills/cloud/gke-observability) |
+| `agent-platform-eval-flywheel` | adjacent | Measures and improves the quality of AI models and agents on Google Cloud using the Eval Quality Flywheel methodology. Use when evaluating an agent or model, building an eval dataset, picking or writing evaluation metrics, analyzing … | [source](https://github.com/google/skills/tree/b15f327/skills/cloud/agent-platform-eval-flywheel) |
+| `agent-platform-alert-configuration` | adjacent | Configures best-practice alerting policies for Google Cloud Vertex AI / Agent Platform agents on Agent Runtime. Use when analyzing, writing, or deploying alerting policies to monitor agent latency, error rates, and quality metrics … | [source](https://github.com/google/skills/tree/b15f327/skills/cloud/agent-platform-alert-configuration) |
+| `google-analytics-admin-api-basics` | adjacent | Manages Google Analytics account and property settings, enables the Analytics Admin API via the Cloud CLI, lists accounts and properties, and manages data streams, custom dimensions, conversion events, and integrations. Use when you need … | [source](https://github.com/google/skills/tree/b15f327/skills/analytics/google-analytics-admin-api-basics) |
+| `google-analytics-data-api-basics` | adjacent | Manages Google Analytics reporting data, enables the Analytics Data API via the Cloud CLI, and creates reports using the Google Analytics Data API (v1beta). Use when you need to interact with Google Analytics properties, run customized … | [source](https://github.com/google/skills/tree/b15f327/skills/analytics/google-analytics-data-api-basics) |
+| `alloydb-basics` | adjacent | Manages clusters, instances, and backups for AlloyDB for PostgreSQL, and integrates with AlloyDB model context protocol (MCP) tools for automated database operations. | [source](https://github.com/google/skills/tree/b15f327/skills/cloud/alloydb-basics) |
+| `google-cloud-networking-observability` | adjacent | Investigates Google Cloud networking issues by analyzing logs, metrics, and diagnostics. Use when investigating VPC Flow Logs (including cost estimation), NAT, firewall, or threat logs, querying latency and throughput metrics, or running … | [source](https://github.com/google/skills/tree/b15f327/skills/cloud/google-cloud-networking-observability) |
+
+## Source: NVIDIA/skills
+
+- Repository: [https://github.com/NVIDIA/skills](https://github.com/NVIDIA/skills) (commit `153b14b`, retrieved 2026-07-14)
+- License: CC-BY-4.0 (skills/docs), Apache-2.0 (code)
+
+| Skill | Tier | What it adds | Upstream |
+|---|---|---|---|
+| `vss-generate-video-report` | core | Use this skill when producing a VSS analysis report — Mode A per-clip VLM, Mode B incident-range via video-analytics. Not for standalone video summarization, real-time alerts or ad-hoc Q&A. | [source](https://github.com/NVIDIA/skills/tree/153b14b/skills/vss-generate-video-report) |
+| `deepstream-dev` | core | NVIDIA DeepStream SDK 9.0 development with Python pyservicemaker API. Use when building video analytics pipelines, GStreamer-based video processing, TensorRT inference integration, object detection/tracking, or Kafka/message broker … | [source](https://github.com/NVIDIA/skills/tree/153b14b/skills/deepstream-dev) |
+| `vss-manage-alerts` | adjacent | Use for VSS alert workflows — real-time monitoring, Alert-Bridge subscriptions, Slack notifications, incident queries, camera onboarding. Not for non-alert analytics. | [source](https://github.com/NVIDIA/skills/tree/153b14b/skills/vss-manage-alerts) |
+| `tao-train-reid` | adjacent | Person re-identification (ReID). Learns discriminative embeddings to match the same person across different camera views, based on metric learning. Use when training, evaluating, exporting, or running inference for a TAO person … | [source](https://github.com/NVIDIA/skills/tree/153b14b/skills/tao-train-reid) |
+| `tao-train-metric-learning-recognition` | adjacent | Metric-learning recognition (ml-recog) for fine-grained visual recognition. Learns embeddings for retrieval-based matching (e.g., retail product recognition) using triplet / contrastive losses. Use when training, evaluating, exporting, or … | [source](https://github.com/NVIDIA/skills/tree/153b14b/skills/tao-train-metric-learning-recognition) |
+| `vss-generate-video-calibration` | adjacent | Use to run AutoMagicCalib on local MP4s, RTSP, or the bundled sample dataset, and to deploy vss-auto-calibration when needed. Do not use for non-AMC calibration or runtime analytics. | [source](https://github.com/NVIDIA/skills/tree/153b14b/skills/vss-generate-video-calibration) |
+| `vss-setup-behavior-analytics` | adjacent | Use to deploy the vss-behavior-analytics service standalone (entrypoint, config-source, optional calibration). Not for the full warehouse deploy. | [source](https://github.com/NVIDIA/skills/tree/153b14b/skills/vss-setup-behavior-analytics) |
+| `vss-setup-video-analytics-api` | adjacent | Use to deploy the vss-video-analytics-api REST service standalone (config-source, data-log bind, Elasticsearch, optional Kafka). Not for full warehouse deploy. | [source](https://github.com/NVIDIA/skills/tree/153b14b/skills/vss-setup-video-analytics-api) |
+| `nv-reason-cxr` | adjacent | Used for command-shape or live NV-Reason-CXR chest X-ray reasoning smoke tests. Not for diagnosis or clinical reporting. | [source](https://github.com/NVIDIA/skills/tree/153b14b/skills/nv-reason-cxr) |
+| `tao-train-depth-anything-v2` | adjacent | Monocular depth estimation using Metric Depth Anything v2 or Relative Depth Anything architectures. Predicts per-pixel depth from single RGB images. Use when training, evaluating, exporting, or running inference for a TAO monocular depth … | [source](https://github.com/NVIDIA/skills/tree/153b14b/skills/tao-train-depth-anything-v2) |
+| `vss-query-analytics` | adjacent | Use this skill when reading video-analytics metrics, incidents, alerts, and sensor data via the VA-MCP server (port 9901). Not for live VLM or incident-range narrative reports. | [source](https://github.com/NVIDIA/skills/tree/153b14b/skills/vss-query-analytics) |
+| `nemo-evaluator-plugin` | adjacent | Use when working on the Evaluator plugin CLI, jobs, SDK-backed specs, metric types, or plugin-owned Evaluator skills. | [source](https://github.com/NVIDIA/skills/tree/153b14b/skills/nemo-evaluator-plugin) |
+
+## Source: phuryn/pm-skills
+
+- Repository: [https://github.com/phuryn/pm-skills](https://github.com/phuryn/pm-skills) (commit `18468a9`, retrieved 2026-07-14)
+- License: MIT
+
+| Skill | Tier | What it adds | Upstream |
+|---|---|---|---|
+| `ab-test-analysis` | core | Analyze A/B test results with statistical significance, sample size validation, confidence intervals, and ship/extend/stop recommendations. Use when evaluating experiment results, checking if a test reached significance, interpreting split … | [source](https://github.com/phuryn/pm-skills/tree/18468a9/pm-data-analytics/skills/ab-test-analysis) |
+| `cohort-analysis` | core | Perform cohort analysis on user engagement data — retention curves, feature adoption trends, and segment-level insights. Use when analyzing user retention by cohort, studying feature adoption over time, investigating churn patterns, or … | [source](https://github.com/phuryn/pm-skills/tree/18468a9/pm-data-analytics/skills/cohort-analysis) |
+| `sql-queries` | core | Generate SQL queries from natural language descriptions. Supports BigQuery, PostgreSQL, MySQL, and other dialects. Reads database schemas from uploaded diagrams or documentation. Use when writing SQL, building data reports, exploring … | [source](https://github.com/phuryn/pm-skills/tree/18468a9/pm-data-analytics/skills/sql-queries) |
+| `dummy-dataset` | core | Generate realistic dummy datasets for testing with customizable columns, constraints, and output formats (CSV, JSON, SQL, Python script). Use when creating test data, building mock datasets, or generating sample data for development and … | [source](https://github.com/phuryn/pm-skills/tree/18468a9/pm-execution/skills/dummy-dataset) |
+| `lean-canvas` | core | Generate a Lean Canvas with problem, solution, metrics, cost structure, UVP, unfair advantage, channels, segments, and revenue. Use when exploring a lean startup canvas, testing a business hypothesis, or modeling a new venture. | [source](https://github.com/phuryn/pm-skills/tree/18468a9/pm-product-strategy/skills/lean-canvas) |
+| `metrics-dashboard` | adjacent | Define and design a product metrics dashboard with key metrics, data sources, visualization types, and alert thresholds. Use when creating a metrics dashboard, defining KPIs, setting up product analytics, or building a data monitoring plan. | [source](https://github.com/phuryn/pm-skills/tree/18468a9/pm-product-discovery/skills/metrics-dashboard) |
+| `gtm-strategy` | adjacent | Create a go-to-market strategy covering marketing channels, messaging, success metrics, and launch timeline. Use when planning a product launch, creating a GTM plan from scratch, or defining a launch strategy for a new market. | [source](https://github.com/phuryn/pm-skills/tree/18468a9/pm-go-to-market/skills/gtm-strategy) |
+| `north-star-metric` | adjacent | Define a North Star Metric and 3-5 supporting input metrics that form a metrics constellation. Classify the business game (Attention, Transaction, Productivity) and validate against 7 criteria for an effective North Star. Use when choosing … | [source](https://github.com/phuryn/pm-skills/tree/18468a9/pm-marketing-growth/skills/north-star-metric) |
+| `product-strategy` | adjacent | Create a comprehensive product strategy using the 9-section Product Strategy Canvas — vision, segments, costs, value propositions, trade-offs, metrics, growth, capabilities, and defensibility. Use when building a product strategy, creating … | [source](https://github.com/phuryn/pm-skills/tree/18468a9/pm-product-strategy/skills/product-strategy) |
--- a/references/berufsbild-de.md
+++ b/references/berufsbild-de.md
@@ -0,0 +1,108 @@
+# Berufsbild (Deutschland) — Statistiker/in
+
+> **Quelle:** BERUFENET, Bundesagentur für Arbeit — Beruf-ID 58778,
+> KldB 2010: B 41114 · via öffentliche BERUFENET-API,
+> abgerufen 2026-07-12. Automatisches Label-Matching
+> (Score 1.00); Inhalte paraphrasiert/gekürzt, Volltext beim
+> Original: https://web.arbeitsagentur.de/berufenet/beruf/58778
+
+## Aufgaben und Tätigkeiten kompakt
+
+Statistiker und Statistikerinnen sammeln und analysieren Daten aus Bereichen wie bspw. Versicherungswesen, Bevölkerungswissenschaft, Bevölkerungsstatistik
+" name="Demografie">Demografie, Sozialwesen, Qualitätsmanagement, Medizin- und Pharmaforschung, Markt- und Meinungsforschung oder naturwissenschaftliche Forschung mithilfe von Modellen und Methoden zur Datenanalyse. Die Ergebnisse dienen als Grundlage für unternehmerische Entscheidungen, liefern Erkenntnisse, z.B. zum Käuferverhalten oder ermöglichen Prognosen und Risikobewertungen. Zudem beraten und unterstützen sie Anwender z.B. bei der Erhebung, Bearbeitung und Interpretation statistischer Daten oder dem Einsatz statistischer Software.
+In der wissenschaftlichen Forschung entwickeln Statistiker und Statistikerinnen bspw. neue statistische Verfahren und Methoden und veröffentlichen ihre Forschungsergebnisse. An Staatliche und staatlich anerkannte Bildungseinrichtung des tertiären Bereichs; dazu zählen forschungsorientierte Universitäten und gleichgestellte Hochschulen, z.B. Kirchliche und Philosophisch-Theologische Hochschulen; sie alle haben das Promotionsrecht; außerdem gibt es praxis- und anwendungsorientierte Fachhochschulen bzw. Hochschulen für angewandte Wissenschaften sowie Duale Hochschulen
+" name="Hochschule (HS)">Hochschulen unterrichten sie Studierende, bereiten Vorlesungen und Seminare vor, korrigieren schriftliche Arbeiten und nehmen Prüfungen ab. Eigenständige wissenschaftliche Tätigkeiten erfordern i.d.R. ein abgeschlossenes Masterstudium und eine Erlangung des Doktorgrades, je nach fachlicher Ausrichtung mit entsprechendem Zusatz, z.B. Dr. phil. (Geisteswissenschaften); befähigt zur eigenständigen Forschung an Universitäten und gleichgestellten Hochschulen; Voraussetzung ist i.d.R. ein Hochschulabschluss, z.B. Master oder Staatsexamen; Promotionsverfahren umfassen eine Doktorarbeit (auch: Dissertation) und eine mündliche Prüfung; Promotionsrecht steht i.d.R. den Universitäten und gleichgestellten Hochschulen zu, Promotionsordnungen der einzelnen Hochschulen regeln das Promotionsverfahren
+" name="Promotion">Promotion.
+
+## Tätigkeitsbezeichnungen
+
+Statistiker/in
+
+Berufsbezeichnung in englischer SpracheStatistician (m/f)
+
+Berufsbezeichnung in französischer SpracheStatisticien/Statisticienne
+
+## Die Tätigkeit im Überblick
+
+Statistiker und Statistikerinnen sammeln und analysieren Daten, bereiten sie auf und stellen sie anschaulich dar. Sie arbeiten z.B. in den Bereichen Markt- und Meinungsforschung, Versicherungswesen, Medizin- und Pharmaforschung, Sozialwesen oder Qualitätsmanagement.
+
+## Aufgaben und Tätigkeiten (Beschreibung)
+
+Worum geht es?Statistiker/innen sammeln und analysieren empirische Daten, bereiten sie auf und stellen sie anschaulich dar, z.B. in den Bereichen Markt- und Meinungsforschung, Versicherungswesen, Medizin- und Pharmaforschung, Sozialwesen oder Qualitätsmanagement.
+Datenerhebung und -auswertungAbhängig vom Ziel einer statistischen Erhebung wählen Statistiker/innen Erhebungs- und Analysemethoden aus (z.B. Total- oder Stichprobenerhebungen mithilfe von Fragebögen oder Interviews) und grenzen Erhebungsbereiche ab. Z.T. organisieren sie die Erhebung auch selbst. Auftraggeber sind z.B. Sozial-, Gesundheits- oder Umweltbehörden, Forscher aus Bereichen wie Medizin, Biologie, Psychologie oder die Industrie. Ist die Erhebung beendet, sichten, beurteilen und interpretieren Statistiker/innen die gewonnenen Daten.
+Im Bereich der medizinischen und pharmazeutischen Forschung geht es z.B. darum, herauszufinden wie hoch die Wahrscheinlichkeit ist, dass eine Person dieselbe Krankheit bekommt, an der schon andere Familienmitglieder leiden, oder wie häufig bei einem Medikament Nebenwirkungen auftreten. Hier unterstützen Statistiker/innen die Forscher beim Erarbeiten von Versuchsansätzen, wirken bei der Überwachung der Versuchsabläufe mit oder werten bereits vorhandenes Datenmaterial aus. 
+In der naturwissenschaftlichen Statistik steht die Erforschung quantitativer Gesetzmäßigkeiten zwischen Merkmalen und Einflussfaktoren im Mittelpunkt, z.B. in der Biologie, Psychologie, Chemie oder Physik. Statistiker/innen beurteilen, ob Unterschiede in den Ergebnissen in Abhängigkeit von vielen Einflussgrößen signifikant sind oder auf Zufall beruhen.
+Vielfältige EinsatzmöglichkeitenIn der Industrie analysieren Statistiker/innen z.B. Daten über Beschäftigungszahlen und Produktivität und liefern so die Grundlage für betriebliche Entscheidungen. Auf dem Gebiet der Unternehmensforschung (auch: Unternehmensforschung, Entscheidungsforschung, Verfahrensforschung
+ Wirtschaft: Sammelbegriff für alle Methoden, Entscheidungen in Unternehmen auf der Grundlage von mathematisch formalisierten und quantifizierten Modellen zu treffen
+" name="Operations Research">Operations Research) erstellen sie Modellrechnungen und werten sie aus. In der Qualitätssicherung überprüfen sie anhand von Stichproben die Einhaltung vorgegebener Sollwerte im Produktionsprozess. Sie erfassen auch die Fehlerart und -häufigkeit, etwa die Verteilung von Maßabweichungen.
+In der empirischen Wirtschaftsforschung und der Entwicklung von
+
+## Aufgaben und Tätigkeiten im Einzelnen
+
+Datenerhebungen organisieren, mit dem Ziel, mit möglichst geringem experimentellem Aufwand verlässliche und optimale Informationen zu erlangen
+
+gewonnene Daten mithilfe entsprechender Software aufbereiten, interpretieren und darstellen (auch grafisch)
+
+Prozesse in Technik, Umwelt, Wirtschaft und Gesellschaft modellieren und simulieren
+
+Datenerhebung und -analysegeeignete Erhebungs- und Aufbereitungsverfahren auswählen, Erhebungsbereich abgrenzen
+
+Fragebögen erarbeiten und gestalten
+
+statistische Hypothesen erstellen und testen (z.B. Schätzen unbekannter Größen)
+
+neue statistische Methoden und Modelle entwickeln
+
+Prüf- und Testverfahren erstellen
+
+statistische Software entwickeln
+
+Modelle und Simulationenan Analysen zum soziologischen und politischen Verhalten sowie an demoskopischen Analysen mitwirken, z.B. in der Markt- und Meinungsforschung
+
+finanz- und versicherungsmathematische Probleme unter statistischen Gesichtspunkten bearbeiten
+
+Qualitätssicherung und PlanungQualitätskontrollen vorbereiten und auswerten, Qualitätsmanagement unterstützen
+
+Nutzung und Auswertung von Datenmengen mithilfe von Datenbanken optimieren, z.B. Personal- und Geschäftsdateien in Unternehmen
+
+Forschung und LehreForschungsprojekte planen und durchführen, ggf. auch interdisziplinär und in Kooperation mit Forschungsinstitutionen
+
+Lehrveranstaltungen im Bereich Statistik/Mathematik (Vorlesungen, Seminare, Übungen, Praktika) konzipieren, vorbereiten und durchführen
+
+Lehrmaterialien, Skripte, Übungs- und Praktikumsanleitungen erarbeiten
+
+Studien- und Prüfungsarbeiten vorbereiten, durchführen und korrigieren
+
+Verwaltungsaufgaben wahrnehmen, Forschungsmittel (Drittmittel) beschaffen
+
+## Berufliche Einsatzmöglichkeiten
+
+Datenerhebung, -analyseDemograf/Demografin
+
+Entwickler/Entwicklerin für Datenvisualisierung
+
+UX-Researcher/UX-Researcherin
+
+Digital-Analyst/Digital-Analystin
+
+Data-Analyst/Data-Analystin
+
+Research-Manager/Research-Managerin
+
+Lehrtätigkeit an HochschulenDozent/Dozentin an Hochschulen und Akademien
+
+Studiengangkoordinator/Studiengangkoordinatorin
+
+Markt-, MeinungsforschungMarktforscher/Marktforscherin
+
+Meinungsforscher/Meinungsforscherin
+
+Verfahrens-, ProduktentwicklungLeiter/Leiterin in der Forschung und Entwicklung
+
+Wissenschaftliche ForschungForschungsreferent/Forschungsreferentin
+
+Leiter einer Forschungsgruppe/Leiterin einer Forschungsgruppe
+
+Konjunkturforscher/Konjunkturforscherin
+
+Wissenschaftlicher Mitarbeiter/Wissenschaftliche Mitarbeiterin
--- a/references/market.md
+++ b/references/market.md
@@ -0,0 +1,189 @@
+# Market evidence report — statistician
+
+Source: **50 real job ads** (JSearch API, countries: us 50), extracted into the MSSQL evidence store; as of 2026-07-20.
+This report contains extracted, aggregated facts only — no ad text is
+reproduced (copyright / platform terms).
+
+## Seniority distribution
+
+| Seniority | Ads | Share |
+|---|---|---|
+| mid | 40 | 80 % |
+| lead | 4 | 8 % |
+| senior | 4 | 8 % |
+| junior | 1 | 2 % |
+| n/a | 1 | 2 % |
+
+## Tools — full market ranking
+
+| # | Item | Ads | Share |
+|---|---|---|---|
+| 1 | SAS | 14 | 28 % |
+| 2 | Python | 13 | 26 % |
+| 3 | SQL | 10 | 20 % |
+| 4 | R programming language | 8 | 16 % |
+| 5 | Microsoft Excel | 7 | 14 % |
+| 6 | R language | 6 | 12 % |
+| 7 | JAVA | 5 | 10 % |
+| 8 | Oracle | 5 | 10 % |
+| 9 | Python programming language | 5 | 10 % |
+| 10 | R (programming language) | 5 | 10 % |
+| 11 | Sybase | 5 | 10 % |
+| 12 | Adobe Acrobat | 4 | 8 % |
+| 13 | Microsoft Word | 4 | 8 % |
+| 14 | Amplitude | 3 | 6 % |
+| 15 | BigQuery | 3 | 6 % |
+| 16 | ClickHouse | 3 | 6 % |
+| 17 | dbt | 3 | 6 % |
+| 18 | KerusCloud | 3 | 6 % |
+| 19 | Microsoft Access | 3 | 6 % |
+| 20 | Mixpanel | 3 | 6 % |
+| 21 | Snowflake | 3 | 6 % |
+
+## Hard skills — full market ranking
+
+| # | Item | Ads | Share |
+|---|---|---|---|
+| 1 | statistical analysis | 32 | 64 % |
+| 2 | data analysis | 15 | 30 % |
+| 3 | experimental design | 10 | 20 % |
+| 4 | causal inference | 7 | 14 % |
+| 5 | data collection | 7 | 14 % |
+| 6 | data interpretation | 7 | 14 % |
+| 7 | machine learning | 7 | 14 % |
+| 8 | sampling | 7 | 14 % |
+| 9 | statistical modeling | 7 | 14 % |
+| 10 | forecasting | 6 | 12 % |
+| 11 | data mining | 5 | 10 % |
+| 12 | data modeling | 5 | 10 % |
+| 13 | graph theory | 5 | 10 % |
+| 14 | link analysis | 5 | 10 % |
+| 15 | natural language processing | 5 | 10 % |
+| 16 | operations research | 5 | 10 % |
+| 17 | quality control | 5 | 10 % |
+| 18 | text analytics | 5 | 10 % |
+| 19 | clinical trial design | 4 | 8 % |
+| 20 | experiment design | 4 | 8 % |
+| 21 | behavioral analytics | 3 | 6 % |
+| 22 | data visualization | 3 | 6 % |
+| 23 | event instrumentation | 3 | 6 % |
+| 24 | hypothesis testing | 3 | 6 % |
+| 25 | predictive modeling | 3 | 6 % |
+| 26 | project management | 3 | 6 % |
+| 27 | proposal writing | 3 | 6 % |
+| 28 | regression modeling | 3 | 6 % |
+| 29 | statistical sampling | 3 | 6 % |
+| 30 | study design | 3 | 6 % |
+| 31 | survey design | 3 | 6 % |
+| 32 | tracking plan design | 3 | 6 % |
+
+## Methods — full market ranking
+
+| # | Item | Ads | Share |
+|---|---|---|---|
+| 1 | crisp-dm | 5 | 10 % |
+| 2 | data science project management | 5 | 10 % |
+| 3 | semma | 5 | 10 % |
+| 4 | a/b testing | 3 | 6 % |
+| 5 | identity resolution | 3 | 6 % |
+| 6 | longitudinal analysis | 3 | 6 % |
+| 7 | machine learning | 3 | 6 % |
+| 8 | power analysis | 3 | 6 % |
+| 9 | statistical rigor | 3 | 6 % |
+
+## Responsibilities — full market ranking
+
+| # | Item | Ads | Share |
+|---|---|---|---|
+| 1 | data analysis | 20 | 40 % |
+| 2 | data preparation | 6 | 12 % |
+| 3 | data visualization | 5 | 10 % |
+| 4 | dataset exploration | 5 | 10 % |
+| 5 | model evaluation | 5 | 10 % |
+| 6 | project execution | 5 | 10 % |
+| 7 | report preparation | 4 | 8 % |
+| 8 | statistical analysis | 4 | 8 % |
+| 9 | client behavior modeling | 3 | 6 % |
+| 10 | client communication | 3 | 6 % |
+| 11 | cross-functional communication | 3 | 6 % |
+| 12 | data instrumentation | 3 | 6 % |
+| 13 | experimentation program ownership | 3 | 6 % |
+| 14 | metric definition | 3 | 6 % |
+| 15 | stakeholder education | 3 | 6 % |
+
+## Regional breakdown
+
+> **Corpus note:** 50 relevant ads in total — below the 100-ad target for a fully reliable ranking. Percentages above should be read as indicative.
+
+### US (us)
+
+50 ads.
+
+**Top hard skills:**
+
+- statistical analysis — 64 % (32 ads)
+- data analysis — 30 % (15 ads)
+- experimental design — 20 % (10 ads)
+- causal inference — 14 % (7 ads)
+- data collection — 14 % (7 ads)
+- data interpretation — 14 % (7 ads)
+- machine learning — 14 % (7 ads)
+- sampling — 14 % (7 ads)
+- statistical modeling — 14 % (7 ads)
+- forecasting — 12 % (6 ads)
+
+**Top tools:**
+
+- SAS — 28 % (14 ads)
+- Python — 26 % (13 ads)
+- SQL — 20 % (10 ads)
+- R programming language — 16 % (8 ads)
+- Microsoft Excel — 14 % (7 ads)
+- R language — 12 % (6 ads)
+- JAVA — 10 % (5 ads)
+- Oracle — 10 % (5 ads)
+- Python programming language — 10 % (5 ads)
+- R (programming language) — 10 % (5 ads)
+
+**Seniority:** mid 80 % · lead 8 % · senior 8 % · junior 2 % · n/a 2 %
+
+### UK (gb)
+
+**Insufficient evidence** — 0 ads (minimum for a regional ranking: 30). No ranking is reported for this region.
+
+### EU/DACH (de, at, ch, nl)
+
+**Insufficient evidence** — 0 ads (minimum for a regional ranking: 30). No ranking is reported for this region.
+
+
+## Job title variants in the market
+
+| Title | Ads |
+|---|---|
+| Statistician | 9 |
+| Mathematical Statistician (Data Scientist) - Direct Hire | 5 |
+| Senior Statistical Analyst | 3 |
+| Lead Statistician HEOR | 2 |
+| Mathematical Statistics Series | 2 |
+| Study Design Statistician (US) | 2 |
+| Supervisory Survey Statistician | 2 |
+| Clinical Research Statistician Remote (DC/MD/VA) | 1 |
+| Data Science Statistician (Applied Analytics) | 1 |
+| Federal Statistician — Insightful Justice Data | 1 |
+| Healthcare Research Scientist | 1 |
+| Lead Statistician at Arena Technical Resources, LLC Springfield, VA | 1 |
+| Mathematical Statistician | 1 |
+| Mathematical Statistician at Census Suitland, MD | 1 |
+| Mathematical Statistician III | 1 |
+| Office Director (Supervisory Mathematical Statistician) | 1 |
+| PPM Data Scientist/Statistician I | 1 |
+| Principal Research Scientist - AI/ML, Applied Statistics & Advanced Analytics | 1 |
+| Principal Scientist, Biostatistics | 1 |
+| Principal Scientist, Biostatistics, Clinical Safety Statistics | 1 |
+| Research Scientist - Statistics | 1 |
+| Senior Statistician/Epidemiologist with Security Clearance | 1 |
+| Senior Strategic Study Design Statistician | 1 |
+| Senior Survey Research Statistician | 1 |
+| Statistical Data Scientist – Injectables and Tech Transfer. | 1 |
+
+Methodology: entities extracted per ad ({hard_skills, tools, methods, responsibilities, seniority}), normalized, counted as DISTINCT ads per entity; report threshold ≥ 3 ads. Headline sections in skills.md/tools.md use the stricter ≥ 20 % threshold.
--- a/references/profile.md
+++ b/references/profile.md
@@ -0,0 +1,36 @@
+# Occupation profile — statistician
+
+- **ESCO URI:** http://data.europa.eu/esco/occupation/ac8b3cd1-a127-4e6a-8208-5cfcf7111955
+- **ESCO code:** 2120.6
+- **ISCO-08 group:** 2120 — Mathematicians, actuaries and statisticians
+- **O*NET-SOC:** 15-2041.00 — Statisticians (match: exactMatch)
+
+## Description (ESCO)
+
+Statisticians collect, tabulate, and, most importantly, analyse quantitative information coming from a varied array of fields. They interpret and analyse statistical studies on fields such as health, demographics, finance, business, etc. and advise based on patterns and drawn analysis.
+
+## Definition
+
+nan
+
+## Alternative labels
+
+- statistic research scientist
+- statistics research scientist
+- statistics specialist
+- statistical scientist
+- statistics scientist
+- statistics research analyst
+- statistical data analyst
+- statistic research associate
+- statistical research scientist
+- statistics researcher
+- statistics scholar
+- statistics science researcher
+- statistics analyst
+- senior statistician
+- statistical science researcher
+- statistical researcher
+- statisticians
+- statistical research analyst
+- statistical scholar
--- a/references/skills.md
+++ b/references/skills.md
@@ -0,0 +1,112 @@
+# Competences — statistician
+
+Source: ESCO v1.2.1 occupation-skill relations (http://data.europa.eu/esco/occupation/ac8b3cd1-a127-4e6a-8208-5cfcf7111955).
+
+## Essential
+
+- **apply for research funding** (skill/competence)
+- **apply research ethics and scientific integrity principles in research activities** (skill/competence)
+- **apply scientific methods** (skill/competence)
+- **apply statistical analysis techniques** (skill/competence)
+- **communicate with a non-scientific audience** (skill/competence)
+- **conduct quantitative research** (skill/competence)
+- **conduct research across disciplines** (skill/competence)
+- **data ethics** (knowledge)
+- **data quality assessment** (knowledge)
+- **data science** (knowledge)
+- **demonstrate disciplinary expertise** (skill/competence)
+- **develop professional network with researchers and scientists** (skill/competence)
+- **digital data processing** (nan)
+- **disseminate results to the scientific community** (skill/competence)
+- **draft scientific or academic papers and technical documentation** (skill/competence)
+- **evaluate research activities** (skill/competence)
+- **execute analytical mathematical calculations** (skill/competence)
+- **gather data** (skill/competence)
+- **identify statistical patterns** (skill/competence)
+- **increase the impact of science on policy and society** (skill/competence)
+- **integrate gender dimension in research** (skill/competence)
+- **interact professionally in research and professional environments** (skill/competence)
+- **manage findable accessible interoperable and reusable data** (skill/competence)
+- **manage intellectual property rights** (skill/competence)
+- **manage open publications** (skill/competence)
+- **manage personal professional development** (skill/competence)
+- **manage research data** (skill/competence)
+- **mathematical modelling** (knowledge)
+- **mathematics** (knowledge)
+- **mentor individuals** (skill/competence)
+- **operate open source software** (skill/competence)
+- **perform data analysis** (skill/competence)
+- **perform project management** (skill/competence)
+- **perform scientific research** (skill/competence)
+- **process data** (skill/competence)
+- **promote open innovation in research** (skill/competence)
+- **promote the participation of citizens in scientific and research activities** (skill/competence)
+- **promote the transfer of knowledge** (skill/competence)
+- **publish academic research** (skill/competence)
+- **quantitative analysis** (knowledge)
+- **research design** (knowledge)
+- **scientific literature** (knowledge)
+- **scientific research methodology** (knowledge)
+- **speak different languages** (skill/competence)
+- **statistical analysis system software** (knowledge)
+- **statistical modeling techniques** (knowledge)
+- **statistics** (knowledge)
+- **synthesise information** (skill/competence)
+- **think abstractly** (skill/competence)
+- **write scientific publications** (skill/competence)
+
+## Optional
+
+- advise on financial matters (skill/competence)
+- advise on legislative acts (skill/competence)
+- algorithms (knowledge)
+- analyse big data (skill/competence)
+- apply blended learning (skill/competence)
+- assist scientific research (skill/competence)
+- biometrics (knowledge)
+- build predictive models (skill/competence)
+- carry out statistical forecasts (skill/competence)
+- computer simulation (knowledge)
+- conduct public surveys (skill/competence)
+- deliver visual presentation of data (skill/competence)
+- demography (knowledge)
+- design questionnaires (skill/competence)
+- develop financial statistics reports (skill/competence)
+- develop scientific theories (skill/competence)
+- develop statistical software (skill/competence)
+- healthcare analytics (knowledge)
+- information confidentiality (knowledge)
+- manage database (skill/competence)
+- manage quantitative data (skill/competence)
+- market research (knowledge)
+- marketing analytics (knowledge)
+- multidisciplinary research (knowledge)
+- opinion poll (knowledge)
+- plan research process (skill/competence)
+- prepare lesson content (skill/competence)
+- present reports (skill/competence)
+- provide lesson materials (skill/competence)
+- set theory (knowledge)
+- social network analysis (knowledge)
+- teach in academic or vocational contexts (skill/competence)
+- use mathematical tools and equipment (skill/competence)
+- use spreadsheets software (skill/competence)
+- write research proposals (skill/competence)
+
+<!-- market-evidence -->
+
+## Market evidence (job-ad analysis, 50 ads, as of 2026-07-20)
+
+Share of analyzed job ads mentioning the item (threshold ≥ 20 %). Source: JSearch/Adzuna APIs.
+
+### Hard skills
+
+- statistical analysis — **64 %**
+- data analysis — **30 %**
+- experimental design — **20 %**
+
+### Responsibilities
+
+- data analysis — **40 %**
+
+<!-- market-evidence -->
--- a/references/tasks.md
+++ b/references/tasks.md
@@ -0,0 +1,45 @@
+# Tasks & work activities — statistician
+
+Source: O*NET 30.3, occupation 15-2041.00 (Statisticians).
+
+## Task statements
+
+- **[Core]** Report results of statistical analyses in peer-reviewed papers and technical manuals.
+- **[Core]** Develop software applications or programming for statistical modeling and graphic analysis.
+- **[Core]** Present statistical and nonstatistical results, using charts, bullets, and graphs, in meetings or conferences to audiences such as clients, peers, and students.
+- **[Core]** Determine whether statistical methods are appropriate, based on user needs or research questions of interest.
+- **[Core]** Report results of statistical analyses, including information in the form of graphs, charts, and tables.
+- **[Core]** Process large amounts of data for statistical modeling and graphic analysis, using computers.
+- **[Core]** Identify relationships and trends in data, as well as any factors that could affect the results of research.
+- **[Core]** Analyze and interpret statistical data to identify significant differences in relationships among sources of information.
+- **[Core]** Prepare data for processing by organizing information, checking for inaccuracies, and adjusting and weighting the raw data.
+- **[Core]** Evaluate the statistical methods and procedures used to obtain data to ensure validity, applicability, efficiency, and accuracy.
+- **[Core]** Evaluate sources of information to determine any limitations, in terms of reliability or usability.
+- **[Core]** Plan data collection methods for specific projects, and determine the types and sizes of sample groups to be used.
+- **[Core]** Design research projects that apply valid scientific techniques, and use information obtained from baselines or historical data to structure uncompromised and efficient analyses.
+- **[Core]** Supervise and provide instructions for workers collecting and tabulating data.
+- **[Core]** Apply sampling techniques, or use complete enumeration bases to determine and define groups to be surveyed.
+- **[Core]** Adapt statistical methods to solve specific problems in many fields, such as economics, biology, and engineering.
+- **[Core]** Develop and test experimental designs, sampling techniques, and analytical methods.
+- **[Core]** Examine theories, such as those of probability and inference, to discover mathematical bases for new or improved methods of obtaining and evaluating numerical data.
+- **[Supplemental]** Prepare and structure data warehouses for storing data.
+
+## Detailed work activities
+
+- Analyze data to identify trends or relationships among variables.
+- Apply mathematical principles or statistical approaches to solve problems in scientific or applied fields.
+- Design research studies to obtain scientific information.
+- Design software applications.
+- Determine appropriate methods for data analysis.
+- Evaluate data quality.
+- Evaluate project designs to determine adequacy or feasibility.
+- Evaluate technical data to determine effect on designs or plans.
+- Implement security measures for computer or information systems.
+- Install computer software.
+- Prepare analytical reports.
+- Prepare data for analysis.
+- Prepare graphics or other visual representations of information.
+- Present research results to others.
+- Supervise information technology personnel.
+- Update knowledge about emerging industry or technology trends.
+- Write computer programming code.
--- a/references/tools.md
+++ b/references/tools.md
@@ -0,0 +1,90 @@
+# Tools & technology — statistician
+
+Source: O*NET 30.3 'Software Skills' for 15-2041.00.
+
+| Software | Category | Hot technology |
+|---|---|---|
+| IBM SPSS Statistics | Analytical or scientific software | yes |
+| SAS | Analytical or scientific software | yes |
+| The MathWorks MATLAB | Analytical or scientific software | yes |
+| Apache Spark | Business intelligence and data analysis software | yes |
+| Tableau | Business intelligence and data analysis software | yes |
+| Apache Hadoop | Data base management system software | yes |
+| Teradata Database | Data base management system software | yes |
+| Amazon Redshift | Data base user interface and query software | yes |
+| Amazon Web Services AWS software | Data base user interface and query software | yes |
+| IBM DB2 | Data base user interface and query software | yes |
+| Microsoft Access | Data base user interface and query software | yes |
+| Microsoft SQL Server | Data base user interface and query software | yes |
+| Structured query language SQL | Data base user interface and query software | yes |
+| Microsoft Visual Basic | Development environment software | yes |
+| Microsoft Visual Basic for Applications VBA | Development environment software | yes |
+| Extensible markup language XML | Enterprise application integration software | yes |
+| SAP software | Enterprise resource planning ERP software | yes |
+| C++ | Object or component oriented development software | yes |
+| Python | Object or component oriented development software | yes |
+| R | Object or component oriented development software | yes |
+| Microsoft Office software | Office suite software | yes |
+| Linux | Operating system software | yes |
+| UNIX | Operating system software | yes |
+| Microsoft PowerPoint | Presentation software | yes |
+| Microsoft Excel | Spreadsheet software | yes |
+| Microsoft Word | Word processing software | yes |
+| Aptech Systems GAUSS | Analytical or scientific software |  |
+| Automatic Forecasting Systems Autobox | Analytical or scientific software |  |
+| Camfit Data Limited Microfit | Analytical or scientific software |  |
+| Cytel StatXact | Analytical or scientific software |  |
+| DataDescription DataDesk | Analytical or scientific software |  |
+| Econometric Software LIMDEP | Analytical or scientific software |  |
+| GraphPad Software GraphPad Prism | Analytical or scientific software |  |
+| IBM SPSS Amos | Analytical or scientific software |  |
+| IBM SPSS AnswerTree | Analytical or scientific software |  |
+| Insightful S-PLUS | Analytical or scientific software |  |
+| Minitab | Analytical or scientific software |  |
+| Muthen & Muthen Mplus | Analytical or scientific software |  |
+| NCSS Power Analysis and Sample Size PASS | Analytical or scientific software |  |
+| Quantitative Micro Software EViews | Analytical or scientific software |  |
+| RAT-STATS | Analytical or scientific software |  |
+| SAS JMP | Analytical or scientific software |  |
+| Scientific Software International SSI Hierarchical Linear and Non-Linear Modeling HLM | Analytical or scientific software |  |
+| Scientific Software International SSI LISREL | Analytical or scientific software |  |
+| StataCorp Stata | Analytical or scientific software |  |
+| Stat-Ease Design-Ease | Analytical or scientific software |  |
+| Stat-Ease Design-Expert | Analytical or scientific software |  |
+| STATISTICA | Analytical or scientific software |  |
+| Statistical software | Analytical or scientific software |  |
+| Statistical Solutions BMDP | Analytical or scientific software |  |
+| StatPoint STATGRAPHICS Centurion | Analytical or scientific software |  |
+| SuperANOVA | Analytical or scientific software |  |
+| Systat Software SigmaPlot | Analytical or scientific software |  |
+| Systat Software SigmaStat | Analytical or scientific software |  |
+| UNISTAT Statistical Package | Analytical or scientific software |  |
+| Visual Numerics TS-WAVE | Analytical or scientific software |  |
+| Wolfram Research Mathematica | Analytical or scientific software |  |
+| XGobi | Analytical or scientific software |  |
+| XLISP-STAT | Analytical or scientific software |  |
+| Qlik Tech QlikView | Business intelligence and data analysis software |  |
+| Apache Pig | Data base management system software |  |
+| Angoss KnowledgeSEEKER | Data mining software |  |
+| NCR Teradata Warehouse Miner | Data mining software |  |
+| SAS Enterprise Miner | Data mining software |  |
+| Common business oriented language COBOL | Development environment software |  |
+| Formula translation/translator FORTRAN | Development environment software |  |
+| SAS/CONNECT | Enterprise application integration software |  |
+| SAP PowerBuilder | Object or component oriented development software |  |
+| Sun Microsystems Java | Object or component oriented development software |  |
+| Microsoft Visual FoxPro | Object oriented data base management software |  |
+
+<!-- market-evidence -->
+
+## Market evidence (job-ad analysis, 50 ads, as of 2026-07-20)
+
+Share of analyzed job ads mentioning the item (threshold ≥ 20 %). Source: JSearch/Adzuna APIs.
+
+### Tools
+
+- SAS — **28 %**
+- Python — **26 %**
+- SQL — **20 %**
+
+<!-- market-evidence -->