# Operations Research Analysts

> Formulate and apply mathematical modeling and other optimizing methods to develop and interpret information that assists management with decisionmaking, policy formulation, or other managerial functions. May collect and analyze data and develop decision support software, services, or products. May develop and supply optimal time, cost, or logistics networks for program evaluation, review, or implementation.

- **SOC code:** 15-2031.00
- **Canonical URL:** https://singulariki.com/roles/role-15-2031-00
- **Also known as:** Analytical Strategist, Operations Research Analyst (Ops Research Analyst), Operations Research Scientist (Ops Research Scientist), Researcher, Advanced Analytics Associate, Decision Analyst, Optimization Analyst, Analytics Consultant
- **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):
- Present the results of mathematical modeling and data analysis to management or other end users.
- Define data requirements, and gather and validate information, applying judgment and statistical tests.
- Perform validation and testing of models to ensure adequacy, and reformulate models, as necessary.
- Prepare management reports defining and evaluating problems and recommending solutions.
- Collaborate with others in the organization to ensure successful implementation of chosen problem solutions.
- Formulate mathematical or simulation models of problems, relating constants and variables, restrictions, alternatives, conflicting objectives, and their numerical parameters.
- Observe the current system in operation, and gather and analyze information about each of the component problems, using a variety of sources.
- Analyze information obtained from management to conceptualize and define operational problems.
- Study and analyze information about alternative courses of action to determine which plan will offer the best outcomes.
- Collaborate with senior managers and decision makers to identify and solve a variety of problems and to clarify management objectives.
- Specify manipulative or computational methods to be applied to models.
- Design, conduct, and evaluate experimental operational models in cases where models cannot be developed from existing data.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Mathematics _(knowledge)_
- Mathematics _(essential_skill)_
- Mathematical Reasoning _(ability)_
- Complex Problem Solving _(transferable_skill)_
- Deductive Reasoning _(ability)_
- Inductive Reasoning _(ability)_
- Computers and Electronics _(knowledge)_
- Reading Comprehension _(essential_skill)_
- Active Listening _(essential_skill)_
- Writing _(essential_skill)_
- Speaking _(essential_skill)_
- Critical Thinking _(essential_skill)_

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

**Tools & technology:**
- Microsoft Excel _(hot technology, in demand)_
- Microsoft Office software _(hot technology, in demand)_
- Microsoft Outlook _(hot technology, in demand)_
- Microsoft Power BI _(hot technology, in demand)_
- Microsoft PowerPoint _(hot technology, in demand)_
- Python _(hot technology, in demand)_
- Salesforce software _(hot technology, in demand)_
- Structured query language SQL _(hot technology, in demand)_
- Tableau _(hot technology, in demand)_
- Amazon Redshift _(hot technology)_
- Apache Hadoop _(hot technology)_
- Apache Hive _(hot technology)_

## AI exposure & outlook

- **AI task-overlap index:** 99th percentile (High) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 96th percentile (High) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 95th percentile (High) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 90th percentile (High) — 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):** 21.5% growth (Growing fast); 9.6k annual openings; 112.1k → 136.2k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $91,290; 107,760 employed.

## How people actually use AI here

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

- **Automation vs augmentation:** 41% automation, 55% augmentation (usage-weighted).
- **Autonomy median:** 4.0 (higher = AI acts more independently).
- **Dominant collaboration mode:** task iteration.

**Tasks most handed to AI here:**
- Prepare management reports defining and evaluating problems and recommending solutions. _(9.7% of measured AI use; task iteration)_
- Break systems into their component parts, assign numerical values to each component, and examine the mathematical relationships between them. _(7.4% of measured AI use; feedback loop)_
- Develop business methods and procedures, including accounting systems, file systems, office systems, logistics systems, and production schedules. _(7.3% of measured AI use; task iteration)_
- Analyze information obtained from management to conceptualize and define operational problems. _(5.3% of measured AI use; task iteration)_
- Study and analyze information about alternative courses of action to determine which plan will offer the best outcomes. _(3.1% of measured AI use; task iteration)_
- Collaborate with senior managers and decision makers to identify and solve a variety of problems and to clarify management objectives. _(2.9% of measured AI use; task iteration)_
- Formulate mathematical or simulation models of problems, relating constants and variables, restrictions, alternatives, conflicting objectives, and their numerical parameters. _(0.9% of measured AI use; directive)_
- Define data requirements and gather and validate information, applying judgment and statistical tests. _(0.4% of measured AI use)_

**Example prompts (honest phrasings of the tasks above — starting points, not endorsed instructions):**
- Help me prepare management reports defining and evaluating problems and recommending solutions.
- Help me break systems into their component parts, assign numerical values to each component, and examine the mathematical relationships between them.
- Help me develop business methods and procedures, including accounting systems, file systems, office systems, logistics systems, and production schedules.
- Help me analyze information obtained from management to conceptualize and define operational problems.
- Help me study and analyze information about alternative courses of action to determine which plan will offer the best outcomes.

## 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-15-2031-00_