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Loading and Moving Machine Operators, Underground Mining

Occupation · SOC 47-5044.00

Operate underground loading or moving machine to load or move coal, ore, or rock using shuttle or mine car or conveyors. Equipment may include power shovels, hoisting engines equipped with cable-drawn scraper or scoop, or machines equipped with gathering arms and conveyor.

Also called: Load Haul Dump Operator (LHD Operator) · Loader Operator · Loading Machine Operator · Shuttle Car Operator · Coal Hauler Operator · Equipment Operator · Miner Operator · Production Miner · Ram Car Operator · Underground Miner · Buggy Driver · Buggy Man

Job family: Construction and Extraction Occupations

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A source-stamped Markdown brief of this occupation — paste it into an agent, or fetch /roles/role-47-5044-00/context.md directly.

AI work map

A fast read on where AI already shows up in this occupation, where it stays a copilot, where humans remain in the loop, and what the labor market is doing. Built from observed Claude.ai conversations mapped to O*NET tasks and from published research — measures of usage and exposure, not advice or predictions that the job is going away.

4th-percentile task overlap — yet about 500 openings a year (-22.3% projected, BLS) . What exposure means →

AI & job outlook

What today's research says about this occupation's exposure to AI, how AI is actually being used in it, and where employment is headed. These are positions within published studies — measures of exposure and usage, not predictions that this job will disappear.

Exposure to current AI

Each study uses its own scale, so the raw scores are not comparable across rows — the percentile (this job's rank among all U.S. occupations with data) is the comparable figure, and sizes the bars.

Measure Rank vs all occupations Percentile Score
LLM task exposure, γ (OpenAI / Eloundou) Low 5th 0.0
AI assistant applicability (Microsoft) Low 10th 0.0

OpenAI's exposure study scores tasks three ways: with a language model alone (α 0.0), with simple added tooling (β 0.0), and including AI-powered software (γ 0.0). Higher means more of the job's tasks could be done at least twice as fast — not that they will be automated away.

Job outlook

Independent U.S. Bureau of Labor Statistics employment projection for 2024–2034 — a labor-market forecast, not an AI-impact forecast.

Outlook Declining · -22.3% by 2034
Projected annual openings 500
Employment 2024 → 2034 6,400 → 5,000

“Annual openings” counts new jobs plus replacements for workers who leave the occupation, so it can be large even when growth is modest.

Tasks

All 28 tasks O*NET lists for this occupation, ordered by importance. Each links to its own page with AI-exposure and observed-use detail.

Work activities

Knowledge, skills & abilities

O*NET importance rating, from 1 (not important) to 5 (extremely important).

Abilities

Control Precision 3.8
Multilimb Coordination 3.4
Reaction Time 3.4
Problem Sensitivity 3.3
Arm-Hand Steadiness 3.3
Manual Dexterity 3.3
Rate Control 3.3
Near Vision 3.3
Perceptual Speed 3.1
Selective Attention 3.1
Time Sharing 3.1
Trunk Strength 3.1
Depth Perception 3.1
Oral Comprehension 3.0
Oral Expression 3.0
Information Ordering 3.0
Category Flexibility 3.0
Visualization 3.0
Extent Flexibility 3.0
Far Vision 3.0
Auditory Attention 3.0
Speech Recognition 3.0
Speech Clarity 3.0
Deductive Reasoning 2.9
Inductive Reasoning 2.9
Finger Dexterity 2.9
Visual Color Discrimination 2.9

Transferable skills

Operation and Control 3.4
Operations Monitoring 3.3
Troubleshooting 3.1
Coordination 3.0
Equipment Maintenance 3.0
Social Perceptiveness 2.9

Knowledge

Mechanical 3.3
Education and Training 3.0

Essential skills

Active Listening 3.0
Speaking 3.0
Critical Thinking 3.0
Reading Comprehension 2.9
Monitoring 2.9

Skills in demand

Skills employers ask for in job postings for this occupation (Lightcast), with whether each is a common or specialized skill.

Tools & technology

Example Category
Microsoft Excel Spreadsheet software Hot technology
Microsoft Outlook Electronic mail software Hot technology
Microsoft PowerPoint Presentation software Hot technology
Microsoft Windows Operating system software Hot technology
Automated systems software Industrial control software
Inventory management systems Inventory management software
Maintenance management software Facilities management software
Mine maintenance software Facilities management software
Work time accounting software Time accounting software

Work context

How characteristic each condition is of the job, on O*NET's 1–5 context scale (higher = more present in day-to-day work). Each condition links to how it varies across all occupations.

Exposed to Contaminants 4.8
Wear Common Protective or Safety Equipment such as Safety Shoes, Glasses, Gloves, Hearing Protection, Hard Hats, or Life Jackets 4.7
Spend Time Using Your Hands to Handle, Control, or Feel Objects, Tools, or Controls 4.6
Face-to-Face Discussions with Individuals and Within Teams 4.5
Exposed to Hazardous Equipment 4.5
Work With or Contribute to a Work Group or Team 4.5
Exposed to Hazardous Conditions 4.5
Exposed to Whole Body Vibration 4.3
In an Open Vehicle or Operating Equipment 4.2
Health and Safety of Other Workers 4.2
Exposed to Sounds, Noise Levels that are Distracting or Uncomfortable 4.1
Exposed to Extremely Bright or Inadequate Lighting Conditions 4.1
Spend Time Making Repetitive Motions 4.0
Exposed to Cramped Work Space, Awkward Positions 3.9
Spend Time Bending or Twisting Your Body 3.8
Pace Determined by Speed of Equipment 3.8
Time Pressure 3.7
Contact With Others 3.7
Determine Tasks, Priorities and Goals 3.6
Consequence of Error 3.6
Frequency of Decision Making 3.5
Importance of Being Exact or Accurate 3.5
Indoors, Not Environmentally Controlled 3.4
Work Outcomes and Results of Other Workers 3.4
Dealing With Unpleasant, Angry, or Discourteous People 3.4
Coordinate or Lead Others in Accomplishing Work Activities 3.3
Spend Time Sitting 3.3
Wear Specialized Protective or Safety Equipment such as Breathing Apparatus, Safety Harness, Full Protection Suits, or Radiation Protection 3.2
Physical Proximity 3.2
Exposed to Minor Burns, Cuts, Bites, or Stings 3.2
Impact of Decisions on Co-workers or Company Results 3.2
Freedom to Make Decisions 3.1
Spend Time Standing 2.8
Spend Time Walking or Running 2.7
Conflict Situations 2.6
Level of Competition 2.6
Exposed to Very Hot or Cold Temperatures 2.6
Importance of Repeating Same Tasks 2.5
In an Enclosed Vehicle or Operate Enclosed Equipment 2.2
Degree of Automation 2.2

How to get in

Job zone
Zone 2 — Job Zone 1-2: Very Little to Some Preparation Needed
Education
Usually requires a high school diploma or GED, though some occupations may not.
Typical entry-level education
No formal educational credential · BLS, the typical path — not a requirement
Related experience
Some occupations may need little or no previous experience; others require several months to a year of experience. For example, landscaping and groundskeeping workers might require very little training or previous experience, while agricultural equipment operators can benefit from on-the job training.
Preparation level
SVP (Below 6.0) — total schooling plus on-the-job experience.

Education of current workers

Share of people in this occupation at each level of education.

High School Diploma 52.6%
Less than a High School Diploma 40.0%
Post-Secondary Certificate 6.2%
Associate's Degree (or other 2-year degree) 1.3%

Interests & work styles

The interests and personal qualities O*NET associates with people who do this work.

Career interests (Holland / RIASEC)

Realistic 7.0
Conventional 3.7
Investigative 2.1

Interest areas

Physical/Manual Labor 6.2
Transportation/Machine Operation 6.1
Mechanics/Electronics 4.3
Engineering 2.5
Construction/Woodwork 1.2
Physical Science 1.1

Work styles

Dependability 3.0
Cautiousness 2.3
Stress Tolerance 2.1
Attention to Detail 1.9
Perseverance 1.5
Integrity 1.4
Self-Control 1.2

Wages & employment

U.S. · annual wages (BLS OEWS)

$48k10th$59k25th$69kMedian$77k75th$83k90th
Annual wages by percentile — U.S. (BLS OEWS). The light band spans the 10th–90th percentile; the darker band is the middle half (25th–75th); the line is the median.
6k20245k2034 (proj.)-22.3% · Declining
Projected U.S. employment, 2024–2034 (BLS Employment Projections). A labor-market forecast for the occupation, not an AI-impact forecast.
10th percentile $48,310
25th percentile $59,130
Median (50th) $68,860
75th percentile $76,820
90th percentile $82,900
People employed 6,130

Industries that employ this occupation

Where these workers are employed, by number of jobs (national, BLS OEWS). Pay shown is the occupation's national median, not industry-specific.

Industry Workers National median pay
Mining, Quarrying, and Oil and Gas Extraction · Sector 5,650 $70,800
Construction · Sector 150 $47,760
Manufacturing · Sector 100 $46,840
Utilities · Sector $94,010
Fossil Fuel Electric Power Generation · National industry $94,010

Where this work is most concentrated

Industries where this occupation is far more common than in the economy as a whole. The location quotient is how many times more concentrated it is here (a value of 5 means five times its economy-wide share).

Industry Concentration Workers
Mining, Quarrying, and Oil and Gas Extraction · Sector 247.81× 5,650
Construction · Sector 0.46× 150
Manufacturing · Sector 0.2× 100

Part of the Energy & Natural Resources career cluster.

Exposure quadrant: AI task-overlap percentile vs Median pay Loading and Moving Machine Operators, Underground Mining sits at the 4th percentile of AI task-overlap and the 60th percentile of median pay, placed here against 12 adjacent occupations on the same two axes. Lower overlap · higher pay Higher overlap · higher pay Higher overlap · lower pay Lower overlap · lower pay Loading and Moving Machine Operators, Underground Mining Industrial Truck and Tractor Operators Continuous Mining Machine Operators Laborers and Freight, Stock, and Material Movers, Hand Hoist and Winch Operators Tank Car, Truck, and Ship Loaders Bus and Truck Mechanics and Diesel Engine Specialists Conveyor Operators and Tenders Crane and Tower Operators AI task-overlap percentile → ↑ Median pay
AI task-overlap percentile (horizontal) vs. median-pay percentile (vertical), across all scored occupations. This occupation is highlighted; related occupations are plotted alongside it. Overlap measures shared tasks with AI, not automation.

Side-by-side comparisons place two occupations’ pay, preparation, skills, and AI exposure on the same page — same data, same scale, no forecast.

What you can do with this

Options the data surfaces for Loading and Moving Machine Operators, Underground Mining — not advice or a forecast. Each is a real cross-link you can follow into the evidence.

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Loading and Moving Machine Operators, Underground Mining show 4th-percentile AI task overlap — and about 500 annual U.S. openings

  • Loading and Moving Machine Operators, Underground Mining rank in the 4th percentile (Low band) for AI task overlap across U.S. occupations — a measure of how much of the work today's AI can attempt, not how much is automated.Eloundou et al. (GPTs are GPTs) + Felten AIOE
  • The occupation is projected to see about 500 U.S. job openings per year (2024–34), counting growth and replacement — a labor-demand projection made independently of AI.BLS Employment Projections 2024–34
  • BLS projects employment to be declining (-22.3%) from 2024 to 2034.BLS Employment Projections 2024–34
  • Median annual pay is $68,860, across about 6,130 U.S. workers.BLS OEWS (May 2024)
Copy the whole kit
Loading and Moving Machine Operators, Underground Mining show 4th-percentile AI task overlap — and about 500 annual U.S. openings

• Loading and Moving Machine Operators, Underground Mining rank in the 4th percentile (Low band) for AI task overlap across U.S. occupations — a measure of how much of the work today's AI can attempt, not how much is automated. (Eloundou et al. (GPTs are GPTs) + Felten AIOE)
• The occupation is projected to see about 500 U.S. job openings per year (2024–34), counting growth and replacement — a labor-demand projection made independently of AI. (BLS Employment Projections 2024–34)
• BLS projects employment to be declining (-22.3%) from 2024 to 2034. (BLS Employment Projections 2024–34)
• Median annual pay is $68,860, across about 6,130 U.S. workers. (BLS OEWS (May 2024))

Source: Singulariki — "Loading and Moving Machine Operators, Underground Mining". https://singulariki.com/roles/role-47-5044-00
Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.

AssetsShare imageMethodology & sourcesPress & newsroomThe newsroom

Every line is built only from figures this page already shows and cites. AI task overlap means what today's AI can attempt — not automation, job loss, or a forecast.

Sources for this page

Every figure above traces to a named public dataset and the exact release below — not hand-written opinion. See the full methodology for what each measure does and does not mean.

Data compiled June 2, 2026. Figures are estimates, not advice.

Cite this page
Plain

Singulariki. "Loading and Moving Machine Operators, Underground Mining." Singulariki: a source-backed encyclopedia of work. Built from O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; Microsoft “Working with AI” working-with-ai; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130. Accessed June 7, 2026. https://singulariki.com/roles/role-47-5044-00

APA

Singulariki. (2026). Loading and Moving Machine Operators, Underground Mining. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-47-5044-00

BibTeX
@misc{singulariki-role-47-5044-00,
  title  = {Loading and Moving Machine Operators, Underground Mining},
  author = {{Singulariki}},
  year   = {2026},
  note   = {O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; Microsoft “Working with AI” working-with-ai; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130. Accessed June 7, 2026},
  url    = {https://singulariki.com/roles/role-47-5044-00}
}

Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.

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