Continuous mining machine operators

SOC 47-5041 · 47-0000 · Score reference month August 2026

Operate self-propelled mining machines that rip coal, metal and nonmetal ores, rock, stone, or sand from the mine face and load it onto conveyors, shuttle cars, or trucks in a continuous operation.

In short

The national Job Market Health score is in the Balanced band for August 2026.

Job Market Health score

50/ 100
Balanced

Weakening · -3

Confidence
High
Restated score
50
Methodology
v1.0
Geography
US
  • At least 90% of required inputs and occupation-industry mapping are covered.

Job Market Health scores are derived indicators based on published data, informational only, not a forecast or guarantee.

$61,810Median annual wageOEWS May 2025
1,400Projected annual openingsBLS Employment Projections 2025-2035
+3.2%Projected growth2025–2035
14,000Total employmentOEWS May 2025

Latest interpretation

What stands out for continuous mining machine operators

The clearest signals from the latest validated score, outlook and metro data.

Long-term outlook is the strongest component

Long-term outlook scores 61/100, compared with 27/100 for occupation fundamentals, a 34-point difference.

JobMarketHealth score components

Published long-term outlook

BLS projects 1,400 average annual openings and +3.2% employment growth from 2025 to 2035. Projected openings are a modeled annual average, not vacancies open today.

BLS Employment Projections

Largest published metro market

Tucson, AZ has the largest published metro employment count for continuous mining machine operators, at 720 jobs. The next-largest published metro is Phoenix-Mesa-Chandler, AZ with 710 jobs. This measures employment scale, not market quality.

BLS OEWS

Local market context

QCEW industry conditions for this occupation’s employment mix

Choose a state to see how the industries that employ this occupation are performing locally.

Choose a state above to explore its available industry context.

How to read this section

QCEW measures employment and wages by industry, not by occupation. We weight those industry conditions using the published industry mix for this occupation. These figures describe the industries that employ this occupation; they are not direct counts of people working in the occupation or jobs currently open.

Source: BLS QCEW. This section is not part of the national 0 to 100 Job Market Health score. See the methodology.

Compare states for continuous mining machine operatorsSide-by-side published industry conditions for two or three states. There is no state-level health score; the 0 to 100 score is national.

How to read this page

The score is a national composite from 0 to 100 that weights near term hiring demand at 50 percent, the occupation's own employment fundamentals at 30 percent, and long-term outlook at 20 percent. Wages and occupation profile details are context shown alongside it, not score inputs. See the full methodology.

Median annual wage and metro employment come from BLS OEWS, which is annual. Projected annual openings and projected growth come from BLS Employment Projections and describe the published projection horizon, so they are not a count of jobs open today. Values shown as not published are suppressed by the source rather than filled in here.

Job Market Health trend

Published composite score · 0–100 · by reference month

Latest published values
  • Aug 2650 / 100
View values: Job Market Health history
Job Market Health history
Reference monthScore / 100
Jan 2543
Feb 2541
Mar 2539
Apr 2542
May 2541
Jun 2545
Jul 2538
Aug 2538
Sep 2537
Oct 2541
Nov 2541
Dec 2543
Jan 2644
Feb 2644
Mar 2644
Apr 2649
May 2657
Jun 2657
Jul 2653
Aug 2650

Score components

The three published inputs behind the composite · each 0–100

Current demand60 / 100
Occupation fundamentals27 / 100
Long-term outlook61 / 100

Largest metro markets by employment

OEWS employment count, where the jobs are, not a quality ranking

OEWS May 2025. These occupation counts describe the survey reference period.

Linked metro names open overall job-market profiles.

Compare cities for this career →

Employment · number of jobs

  • Tucson, AZ720
  • Phoenix-Mesa-Chandler, AZ710
  • Salt Lake City-Murray, UT380
  • Pittsburgh, PA140
  • Beckley, WV120
  • St. Louis, MO-IL120
  • Wheeling, WV-OH120
  • Kansas City, MO-KS100
  • Charleston, WV70
  • Detroit-Warren-Dearborn, MI60
Largest metro markets by employment
Metro areaEmploymentJobs per 1,000Median annual wage
Tucson, AZ7201.85$60,880
Phoenix-Mesa-Chandler, AZ7100.30$63,250
Salt Lake City-Murray, UT3800.46$57,900
Pittsburgh, PA1400.13$60,780
Beckley, WV1202.88$64,270
St. Louis, MO-IL1200.09$48,120
Wheeling, WV-OH1202.12$66,300
Kansas City, MO-KS1000.09$47,950
Charleston, WV700.69$65,280
Detroit-Warren-Dearborn, MI600.03$54,690

Education & training

Typical entry requirements · BLS Employment Projections 2025-2035

Typical education
No formal educational credential
Work experience
None
On-the-job training
Moderate-term on-the-job training
Projected employment
14,400 jobs

Top skills

Occupation profile · O*NET 31.0 Database

  • Operation and Control
  • Operations Monitoring
  • Equipment Maintenance
  • Critical Thinking
  • Troubleshooting
  • Judgment and Decision Making
  • Repairing
  • Active Listening
  • Complex Problem Solving
  • Monitoring

Also known as: Bore Miner Operator, Continuous Miner, Continuous Miner Operator (CMO), Continuous Mining Machine Operator, Continuous Mining Operator (CMO), Heavy Equipment Operator

AI & this occupation

How AI relates to Continuous mining machine operators work

Across 4 research exposure measures, Continuous mining machine operators is in the lower technical AI exposure band based on the mean of the available source-specific percentile ranks. Exposure describes how much of the work the studied AI capabilities could technically assist with; it is not a forecast of job loss.

The saved Anthropic task-exposure benchmark records a zero index for this occupation. This is not proof of no AI use; the observation window is not recorded in this saved release.

JobMarketHealth has not measured an AI effect on this occupation's employment or wages, and these figures do not enter its scores; there is no clear evidence of displacement in the data shown here.

Technical AI exposureLower exposureMean of 4 available source-specific percentile ranks (4 measures checked); fixed exposure bands, not a national rank of the composite
Dated Claude task exposureLower thirdObserved task-exposure benchmark 0.000; observation window not recorded
Business AI use (BTOS Core)24.6%U.S. businesses using AI, two weeks ending 2026-10-04; all industries, not this occupation
Historical task mix (2025)Not enough tasksFewer than 3 observed tasks
Measured labor-market effectNot estimatedJobMarketHealth does not attribute employment or wage changes to AI

Exposure measures (kept separate)

  • GPTs are GPTs exposure (β, GPT-4 rated): 0.00 of 1, national percentile 3 (lower third)
  • Microsoft AI applicability: 0.04 of 1, national percentile 10 (lower third)
  • AIOE (Felten, Raj & Seamans): -1.17 (standardized), national percentile 13 (lower third)
  • OECD AI Capability Gap (lower gap = higher potential exposure): gap 3.9 of 23, national percentile 40 (middle third)
OECD capability gap by domain

As published by the OECD: the gap between what the occupation demands (0-5) and current AI capability in each domain. A lower gap means AI is closer to the requirement (higher potential exposure); 0 means AI already meets it or the domain is not relevant.

  • Language: gap 0.00 (demand 1.30 of 5)
  • Social interaction: gap 0.15 (demand 2.15 of 5)
  • Problem solving: gap 0.50 (demand 2.50 of 5)
  • Creativity: gap 0.00 (demand 1.00 of 5)
  • Metacognition & critical thinking: gap 0.20 (demand 2.20 of 5)
  • Knowledge, learning & memory: gap 0.25 (demand 3.25 of 5)
  • Vision: gap 0.70 (demand 3.70 of 5)
  • Manipulation: gap 1.60 (demand 3.60 of 5)
  • Robotic intelligence: gap 1.95 (demand 3.95 of 5)

National context: what businesses used generative AI for

From the Census 2025-26 BTOS AI Supplement (all industries; businesses whose employees used generative AI). Census did not measure Continuous mining machine operators specifically.

  • Writing or editing documents, emails, or communications: 85.4%
  • Searching for information or technical help: 49.9%
  • Interpreting, analyzing, translating, or summarizing documents: 44.6%
  • Information processing, paperwork, or filing: 34.7%

Exposure and observed usage are separate measures and neither equals job loss. Census BTOS figures are business-level surveys and are not occupation-specific. Sources: GPTs are GPTs occupation exposure; Microsoft Working with AI: AI applicability; AI Occupational Exposure (AIOE); OECD AI Exposure Measure (AI Capability Gap); Anthropic Economic Index; Census BTOS Core AI Use; Census BTOS AI Supplement 2025-26. These figures do not affect Job Market Health scores. Explore AI & Jobs · How we use AI data.

Sources and methodology

The datasets behind the figures on this page

Job Market Health score
Score for reference month August 2026 · methodology v1.0 · MethodologyScore last recalculated Oct 2, 2026 · First published Sep 29, 2026
BLS Occupational Employment and Wage Statistics
Employment, wages and largest metros · OEWS May 2025 · publisher release May 15, 2026 · About this sourceRetrieved Sep 17, 2026
BLS Employment Projections
Projected growth, openings, education and training · BLS Employment Projections 2025-2035 · publisher release Aug 27, 2026 · About this sourceRetrieved Sep 17, 2026
O*NET
Skills, alternate titles and related occupations · O*NET 31.0 Database · publisher release date not verified · About this sourceRetrieved Oct 19, 2026

Values marked “Not published” are suppressed or not published by the source. We leave them blank rather than estimating them. Pipeline status for every source is on Data Status.

Evidence record

JobMarketHealth derived indicator; not a government statistic. The composite score is national and occupation level.

Occupation
Continuous mining machine operators
SOC code
47-5041
Geography
United States
Reference month
August 2026
Published Job Market Health score
50 / 100
Restated score
50 / 100
Band
Balanced
Current Demand component
60 / 10050% weight
Occupation Fundamentals component
27 / 10030% weight
Long-Term Outlook component
61 / 10020% weight
Confidence
HighAt least 90% of required inputs and occupation-industry mapping are covered.
Methodology version
v1.0
Source vintage: Annual
EP-2025-2035|CPS-25b-2025|OEWS-2020-2025
Source vintage: Monthly calculated at
2026-10-02T15:32:41.029Z
First published at
Sep 29, 2026
Recalculated at
Oct 2, 2026
Canonical record URL
https://jobmarkethealth.com/occupations/continuous-mining-machine-operators#evidence-record
Derived by
JobMarketHealth

Keep going

Learn how to judge a market from these numbers in how to tell if a job market is healthy, or why projected growth and annual openings often disagree in projected growth vs projected annual openings. Coverage, revisions and limits are explained on about the data.

The datasets behind these figures, and what each one can and cannot show, are set out on data sources.