# Climate Change Policy Analysts

> Research and analyze policy developments related to climate change. Make climate-related recommendations for actions such as legislation, awareness campaigns, or fundraising approaches.

- **SOC code:** 19-2041.01
- **Canonical URL:** https://singulariki.com/roles/role-19-2041-01
- **Also known as:** Climate Analyst, Climate and Energy Program Associate, Environmental Policy Analyst, Policy Analyst, Climate Advisor, Climate Economist, Policy Associate, Policy Research Associate
- **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):
- Provide analytical support for policy briefs related to renewable energy, energy efficiency, or climate change.
- Propose new or modified policies involving use of traditional and alternative fuels, transportation of goods, and other factors relating to climate and climate change.
- Prepare study reports, memoranda, briefs, testimonies, or other written materials to inform government or environmental groups on environmental issues, such as climate change.
- Analyze and distill climate-related research findings to inform legislators, regulatory agencies, or other stakeholders.
- Make legislative recommendations related to climate change or environmental management, based on climate change policies, principles, programs, practices, and processes.
- Present climate-related information at public interest, governmental, or other meetings.
- Promote initiatives to mitigate climate change with government or environmental groups.
- Gather and review climate-related studies from government agencies, research laboratories, and other organizations.
- Review existing policies or legislation to identify environmental impacts.
- Research policies, practices, or procedures for climate or environmental management.
- Write reports or academic papers to communicate findings of climate-related studies.
- Develop, or contribute to the development of, educational or outreach programs on the environment or climate change.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Reading Comprehension _(essential_skill)_
- Written Comprehension _(ability)_
- Active Listening _(essential_skill)_
- Critical Thinking _(essential_skill)_
- Oral Comprehension _(ability)_
- Oral Expression _(ability)_
- Written Expression _(ability)_
- Deductive Reasoning _(ability)_
- Inductive Reasoning _(ability)_
- Law and Government _(knowledge)_
- Writing _(essential_skill)_
- Speaking _(essential_skill)_

**Skills in demand:**
- Reading Comprehension _(Common Skill)_
- Inductive Reasoning _(Common Skill)_
- Deductive Reasoning _(Common Skill)_
- Critical Thinking _(Common Skill)_
- Active Listening _(Common Skill)_
- Writing _(Common Skill)_
- English Language _(Common Skill)_
- Complex Problem Solving _(Common Skill)_
- Active Learning _(Common Skill)_
- Systems Analysis _(Specialized Skill)_
- Microsoft PowerPoint _(Common Skill)_
- Microsoft Excel _(Common Skill)_

**Tools & technology:**
- Microsoft Excel _(hot technology, in demand)_
- Microsoft Office software _(hot technology, in demand)_
- Microsoft PowerPoint _(hot technology, in demand)_
- C++ _(hot technology)_
- ESRI ArcGIS software _(hot technology)_
- Linux _(hot technology)_
- Microsoft Word _(hot technology)_
- Perl _(hot technology)_
- Python _(hot technology)_
- R _(hot technology)_
- SAS _(hot technology)_
- The MathWorks MATLAB _(hot technology)_

## AI exposure & outlook

- **AI task-overlap index:** 78th percentile (High) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 75th percentile (High) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 95th percentile (High) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 60th percentile (Moderate) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 20th percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** yes — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** 4.4% growth (About average); 8.5k annual openings; 90.3k → 94.3k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $80,060; 84,930 employed.

## How people actually use AI here

Anthropic Economic Index — measured AI conversations mapped to this occupation's tasks:

- **Automation vs augmentation:** 31% automation, 51% augmentation (usage-weighted).
- **Autonomy median:** 3.0 (higher = AI acts more independently).
- **Dominant collaboration mode:** task iteration.

**Tasks most handed to AI here:**
- Develop, or contribute to the development of, educational or outreach programs on the environment or climate change. _(0.8% of measured AI use; directive)_
- Propose new or modified policies involving use of traditional and alternative fuels, transportation of goods, and other factors relating to climate and climate change. _(0.5% of measured AI use; task iteration)_
- Prepare study reports, memoranda, briefs, testimonies, or other written materials to inform government or environmental groups on environmental issues such as climate change. _(0.5% of measured AI use; directive)_

**Example prompts (honest phrasings of the tasks above — starting points, not endorsed instructions):**
- Help me develop, or contribute to the development of, educational or outreach programs on the environment or climate change.
- Help me propose new or modified policies involving use of traditional and alternative fuels, transportation of goods, and other factors relating to climate and climate change.
- Help me prepare study reports, memoranda, briefs, testimonies, or other written materials to inform government or environmental groups on environmental issues such as climate change.

## 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-19-2041-01_