# Survey Researchers

> Plan, develop, or conduct surveys. May analyze and interpret the meaning of survey data, determine survey objectives, or suggest or test question wording. Includes social scientists who primarily design questionnaires or supervise survey teams.

- **SOC code:** 19-3022.00
- **Canonical URL:** https://singulariki.com/roles/role-19-3022-00
- **Also known as:** Research Associate, Research Scientist, Survey Methodologist, Survey Researcher, Data Analyst, Market Survey Representative, Research Fellow, Research Interviewer
- **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):
- Conduct surveys and collect data, using methods such as interviews, questionnaires, focus groups, market analysis surveys, public opinion polls, literature reviews, and file reviews.
- Prepare and present summaries and analyses of survey data, including tables, graphs, and fact sheets that describe survey techniques and results.
- Consult with clients to identify survey needs and specific requirements, such as special samples.
- Determine and specify details of survey projects, including sources of information, procedures to be used, and the design of survey instruments and materials.
- Support, plan, and coordinate operations for single or multiple surveys.
- Monitor and evaluate survey progress and performance, using sample disposition reports and response rate calculations.
- Collaborate with other researchers in the planning, implementation, and evaluation of surveys.
- Conduct research to gather information about survey topics.
- Direct and review the work of staff members, including survey support staff and interviewers who gather survey data.
- Direct updates and changes in survey implementation and methods.
- Produce documentation of the questionnaire development process, data collection methods, sampling designs, and decisions related to sample statistical weighting.
- Write proposals to win new projects.

## Skills, tools, capabilities

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

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

**Tools & technology:**
- IBM SPSS Statistics _(hot technology, in demand)_
- Microsoft Excel _(hot technology, in demand)_
- Microsoft Office software _(hot technology, in demand)_
- Microsoft PowerPoint _(hot technology, in demand)_
- Python _(hot technology, in demand)_
- R _(hot technology, in demand)_
- SAS _(hot technology, in demand)_
- C++ _(hot technology)_
- Extensible markup language XML _(hot technology)_
- JavaScript _(hot technology)_
- Microsoft Access _(hot technology)_
- Microsoft Active Server Pages ASP _(hot technology)_

## AI exposure & outlook

- **AI task-overlap index:** 80th percentile (High) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 97th percentile (High) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 95th percentile (High) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 43rd percentile (Moderate) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 35th percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** yes — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** -5.2% growth (Declining); 0.7k annual openings; 8.8k → 8.3k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $63,380; 7,720 employed.

## How people actually use AI here

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

- **Automation vs augmentation:** 52% automation, 42% augmentation (usage-weighted).
- **Autonomy median:** 3.0 (higher = AI acts more independently).
- **Dominant collaboration mode:** directive.

**Tasks most handed to AI here:**
- Conduct research to gather information about survey topics. _(5.2% of measured AI use; directive)_
- Review, classify, and record survey data in preparation for computer analysis. _(3.3% of measured AI use; directive)_
- Prepare and present summaries and analyses of survey data, including tables, graphs, and fact sheets that describe survey techniques and results. _(2.5% of measured AI use; directive)_
- Analyze data from surveys, old records, or case studies, using statistical software. _(1.0% of measured AI use; directive)_

**Example prompts (honest phrasings of the tasks above — starting points, not endorsed instructions):**
- Help me conduct research to gather information about survey topics.
- Help me review, classify, and record survey data in preparation for computer analysis.
- Help me prepare and present summaries and analyses of survey data, including tables, graphs, and fact sheets that describe survey techniques and results.
- Help me analyze data from surveys, old records, or case studies, using statistical software.

## 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-19-3022-00_