# Railroad Conductors and Yardmasters

> Coordinate activities of switch-engine crew within railroad yard, industrial plant, or similar location. Conductors coordinate activities of train crew on passenger or freight trains. Yardmasters review train schedules and switching orders and coordinate activities of workers engaged in railroad traffic operations, such as the makeup or breakup of trains and yard switching.

- **SOC code:** 53-4031.00
- **Canonical URL:** https://singulariki.com/roles/role-53-4031-00
- **Also known as:** Conductor, Freight Conductor, Railroad Conductor, Yardmaster, Train Master, Trainman, Car Chaser, Car Dispatcher
- **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):
- Signal engineers to begin train runs, stop trains, or change speed, using telecommunications equipment or hand signals.
- Confer with engineers regarding train routes, timetables, and cargoes, and to discuss alternative routes when there are rail defects or obstructions.
- Instruct workers to set warning signals in front and at rear of trains during emergency stops.
- Receive information regarding train or rail problems from dispatchers or from electronic monitoring devices.
- Direct and instruct workers engaged in yard activities, such as switching tracks, coupling and uncoupling cars, and routing inbound and outbound traffic.
- Receive instructions from dispatchers regarding trains' routes, timetables, and cargoes.
- Operate controls to activate track switches and traffic signals.
- Keep records of the contents and destination of each train car, and make sure that cars are added or removed at proper points on routes.
- Observe yard traffic to determine tracks available to accommodate inbound and outbound traffic.
- Arrange for the removal of defective cars from trains at stations or stops.
- Direct engineers to move cars to fit planned train configurations, combining or separating cars to make up or break up trains.
- Inspect each car periodically during runs.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Oral Expression _(ability)_
- Public Safety and Security _(knowledge)_
- Transportation _(knowledge)_
- Oral Comprehension _(ability)_
- Problem Sensitivity _(ability)_
- Speaking _(essential_skill)_
- Monitoring _(essential_skill)_
- Coordination _(transferable_skill)_
- Critical Thinking _(essential_skill)_
- Near Vision _(ability)_
- Far Vision _(ability)_
- Speech Recognition _(ability)_

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

**Tools & technology:**
- Microsoft Office software _(hot technology, in demand)_
- Microsoft Excel _(hot technology)_
- Microsoft Outlook _(hot technology)_
- Microsoft PowerPoint _(hot technology)_
- Microsoft Word _(hot technology)_
- Automated equipment identification AEI software
- Bourque Data Systems YardMaster
- Freight reservation software
- Inventory tracking software
- Positive train control PTC systems
- RailComm DocYard
- SAIC government services and IT support software

## AI exposure & outlook

- **AI task-overlap index:** 41st percentile (Moderate) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 36th percentile (Moderate) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 42nd percentile (Moderate) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 52nd percentile (Moderate) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 68th percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** no — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** 1.1% growth (About average); 3.1k annual openings; 36.8k → 37.2k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $74,080; 42,710 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-53-4031-00_