# Biologists

> Research or study basic principles of plant and animal life, such as origin, relationship, development, anatomy, and functions.

- **SOC code:** 19-1029.04
- **Canonical URL:** https://singulariki.com/roles/role-19-1029-04
- **Also known as:** Biologist, Botanist, Fisheries and Wildlife Biologist, Scientist, Aquatic Biologist, Biological Scientist, Fisheries Biologist, Marine Biologist
- **Frame:** "AI exposure" means task overlap (how codifiable the work is), not jobs lost or a forecast. Every figure below is traced to a named public dataset.

## What this work is

**Core tasks** (O*NET):
- Research environmental effects of present and potential uses of land and water areas, determining methods of improving environmental conditions or such outputs as crop yields.
- Program and use computers to store, process, and analyze data.
- Prepare technical and research reports, such as environmental impact reports, and communicate the results to individuals in industry, government, or the general public.
- Supervise biological technicians and technologists and other scientists.
- Develop and maintain liaisons and effective working relations with groups and individuals, agencies, and the public to encourage cooperative management strategies or to develop information and interpret findings.
- Identify, classify, and study structure, behavior, ecology, physiology, nutrition, culture, and distribution of plant and animal species.
- Study basic principles of plant and animal life, such as origin, relationship, development, anatomy, and function.
- Collect and analyze biological data about relationships among and between organisms and their environment.
- Review reports and proposals, such as those relating to land use classifications and recreational development, for accuracy, adequacy, or adherence to policies, regulations, or scientific standards.
- Study aquatic plants and animals and environmental conditions affecting them, such as radioactivity or pollution.
- Study and manage wild animal populations.
- Write grant proposals to obtain funding for biological research.

**Emerging tasks** (O*NET):
- Inventory and order lab supplies.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Biology _(knowledge)_
- Science _(essential_skill)_
- Education and Training _(knowledge)_
- Reading Comprehension _(essential_skill)_
- Writing _(essential_skill)_
- Oral Comprehension _(ability)_
- Written Comprehension _(ability)_
- Written Expression _(ability)_
- Inductive Reasoning _(ability)_
- English Language _(knowledge)_
- Active Listening _(essential_skill)_
- Speaking _(essential_skill)_

**Skills in demand:**
- Biology _(Specialized Skill)_
- Writing _(Common Skill)_
- Reading Comprehension _(Common Skill)_
- Inductive Reasoning _(Common Skill)_
- English Language _(Common Skill)_
- Information Ordering _(Specialized Skill)_
- Critical Thinking _(Common Skill)_
- Active Listening _(Common Skill)_
- Mathematics _(Common Skill)_
- Deductive Reasoning _(Common Skill)_
- Active Learning _(Common Skill)_
- Speech Recognition _(Specialized Skill)_

**Tools & technology:**
- Microsoft Excel _(hot technology, in demand)_
- Microsoft Office software _(hot technology, in demand)_
- Python _(hot technology, in demand)_
- R _(hot technology, in demand)_
- Adobe Photoshop _(hot technology)_
- C++ _(hot technology)_
- ESRI ArcGIS software _(hot technology)_
- IBM SPSS Statistics _(hot technology)_
- Linux _(hot technology)_
- Microsoft Access _(hot technology)_
- Microsoft PowerPoint _(hot technology)_
- Microsoft Word _(hot technology)_

## AI exposure & outlook

- **AI task-overlap index:** 70th percentile (High) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 74th percentile (High) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 60th percentile (Moderate) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 77th percentile (High) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 11th percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** yes — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** 1.2% growth (About average); 4.8k annual openings; 63.7k → 64.5k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $93,330; 59,710 employed.

## Sources

- **O*NET** (30.3) — U.S. Department of Labor / National Center for O*NET Development. https://www.onetcenter.org/database.html
- **BLS Occupational Employment and Wage Statistics (OEWS)** (May 2024) — U.S. Bureau of Labor Statistics. https://www.bls.gov/oes/
- **BLS Employment Projections** (2024–2034) — U.S. Bureau of Labor Statistics. https://www.bls.gov/emp/
- **Anthropic Economic Index** (v4 (2026-01-15) + v2 (2025-03-27)) — Anthropic. https://www.anthropic.com/economic-index
- **Microsoft “Working with AI”** (working-with-ai) — Microsoft Research. https://www.microsoft.com/en-us/research/
- **“GPTs are GPTs” (Eloundou et al.)** (arXiv 2303.10130) — OpenAI / academic. https://arxiv.org/abs/2303.10130
- **AI Occupational Exposure (AIOE)** (Felten, Raj & Seamans) — academic. https://github.com/AIOE-Data/AIOE
- **Frey & Osborne (2013)** (frey-osborne-automation) — academic. https://www.oxfordmartin.ox.ac.uk/publications/the-future-of-employment/
- **Dingel & Neiman (2020)** (dingel-neiman-workathome) — academic. https://github.com/jdingel/DingelNeiman-workathome

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_Generated from Singulariki's joined dataset; data snapshot 2026-06-02T21:00:32.945303+00:00. https://singulariki.com/roles/role-19-1029-04_