Skip to content
Singulariki

Sailors and Marine Oilers

Occupation · SOC 53-5011.00

Stand watch to look for obstructions in path of vessel, measure water depth, turn wheel on bridge, or use emergency equipment as directed by captain, mate, or pilot. Break out, rig, overhaul, and store cargo-handling gear, stationary rigging, and running gear. Perform a variety of maintenance tasks to preserve the painted surface of the ship and to maintain line and ship equipment. Must hold government-issued certification and tankerman certification when working aboard liquid-carrying vessels. Includes able seamen and ordinary seamen.

Also called: Able Bodied Seaman (AB Seaman) · Able Seaman · Deck Hand · Deckhand · Able Bodied Watchman (AB Watchman) · Boat Crew Deck Hand · Bosun · Deckhand Engineer · Oiler · Tankerman · Aerographer's Mate · Barge Hand

Job family: Transportation and Material Moving Occupations

Take this to your AI
Download .md

A source-stamped Markdown brief of this occupation — paste it into an agent, or fetch /roles/role-53-5011-00/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.

8th-percentile task overlap — yet about 3,900 openings a year (+2.3% 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
Overall AI exposure (Felten et al.) Low 12th -1.2
LLM task exposure, γ (OpenAI / Eloundou) Low 9th 0.1
AI assistant applicability (Microsoft) Low 15th 0.1

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 0.1). Higher means more of the job's tasks could be done at least twice as fast — not that they will be automated away.

This job mostly cannot be done remotely (Dingel–Neiman) — its hands-on tasks sit outside what software-based AI reaches.

Mixed signals. Today's AI/LLM studies show relatively low exposure for this job, but the older (2013) Frey–Osborne work rated it higher for computerization and robotics. Different eras, different technologies — the AI measures above reflect the current state.

Historical automation estimate (2013)

A pre-LLM (2013) estimate of how automatable this job is by computerization and robotics. Shown for historical context only — it is not part of any current AI ranking.

Frey–Osborne probability 0.8 · 68th percentile among occupations · High

Job outlook

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

Outlook About average · +2.3% by 2034
Projected annual openings 3,900
Employment 2024 → 2034 32,100 → 32,800

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

Where this work sits on the global GenAI gradient

The ILO's 2025 global study scores generative-AI exposure on the international ISCO-08 occupation system, not US SOC. Bridged through the published (and approximate, many-to-many) IBS O*NET-SOC ↔ ISCO-08 crosswalk, this US occupation corresponds to the international occupation below. Exposure here means how much of the work's tasks today's AI can attempt — task overlap, not automation, adoption, or jobs lost.

14% mean task exposure (2025)
15th percentile of 427 placed occupations
+2 pts shift 2023 → 2025
International occupation (ISCO-08) Task exposure (2025) Most tasks fall in
Ships' Deck Crews and Related Workers · 8350 14% Not exposed

Read the whole six-band gradient on the GenAI exposure gradient page. The crosswalk is approximate: a US occupation can map to several international ones, and the ILO scores describe the international occupation, not this exact US role.

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

Far Vision 4.0
Control Precision 3.9
Oral Comprehension 3.8
Problem Sensitivity 3.8
Perceptual Speed 3.8
Depth Perception 3.8
Arm-Hand Steadiness 3.6
Multilimb Coordination 3.6
Auditory Attention 3.6
Manual Dexterity 3.5
Visual Color Discrimination 3.4
Flexibility of Closure 3.3
Selective Attention 3.3
Near Vision 3.3
Hearing Sensitivity 3.3
Oral Expression 3.1
Deductive Reasoning 3.1
Inductive Reasoning 3.1
Information Ordering 3.1
Visualization 3.1
Reaction Time 3.1
Static Strength 3.1
Extent Flexibility 3.1
Gross Body Equilibrium 3.1
Speech Recognition 3.1
Speech Clarity 3.1

Transferable skills

Operations Monitoring 3.9
Operation and Control 3.6
Troubleshooting 3.1
Repairing 3.1
Coordination 3.0
Complex Problem Solving 3.0
Quality Control Analysis 3.0
Judgment and Decision Making 3.0

Essential skills

Monitoring 3.3
Active Listening 3.1
Critical Thinking 3.1
Speaking 3.0

Knowledge

Public Safety and Security 3.2
Transportation 3.1

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 Office software Office suite software Hot technology
Microsoft Outlook Electronic mail software Hot technology
Microsoft PowerPoint Presentation software Hot technology
Microsoft Windows Operating system software Hot technology
Microsoft Word Word processing software Hot technology
Computerized maintenance management system CMMS Facilities management software
KNMI TurboWin Data base user interface and query software
Kongsberg Maritime K-Log Deck Logbook Data base user interface and query software
Log book software Data base user interface and query 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.

Outdoors, Exposed to All Weather Conditions 5.0
Wear Common Protective or Safety Equipment such as Safety Shoes, Glasses, Gloves, Hearing Protection, Hard Hats, or Life Jackets 5.0
Exposed to Sounds, Noise Levels that are Distracting or Uncomfortable 5.0
Exposed to Very Hot or Cold Temperatures 4.9
Exposed to Contaminants 4.6
Health and Safety of Other Workers 4.5
Contact With Others 4.4
Spend Time Using Your Hands to Handle, Control, or Feel Objects, Tools, or Controls 4.3
Face-to-Face Discussions with Individuals and Within Teams 4.3
Importance of Being Exact or Accurate 4.3
Consequence of Error 4.2
Spend Time Standing 4.2
Work Outcomes and Results of Other Workers 4.1
Work With or Contribute to a Work Group or Team 4.0
Time Pressure 4.0
Spend Time Bending or Twisting Your Body 3.9
Exposed to Minor Burns, Cuts, Bites, or Stings 3.8
Physical Proximity 3.8
Spend Time Walking or Running 3.7
Determine Tasks, Priorities and Goals 3.7
Exposed to Hazardous Equipment 3.7
Spend Time Making Repetitive Motions 3.6
Impact of Decisions on Co-workers or Company Results 3.6
Frequency of Decision Making 3.6
Exposed to Cramped Work Space, Awkward Positions 3.6
Coordinate or Lead Others in Accomplishing Work Activities 3.6
Importance of Repeating Same Tasks 3.4
Exposed to Hazardous Conditions 3.3
E-Mail 3.2
Exposed to Extremely Bright or Inadequate Lighting Conditions 3.1
Dealing With Unpleasant, Angry, or Discourteous People 3.1
Freedom to Make Decisions 3.1
Exposed to High Places 3.0
Spend Time Keeping or Regaining Balance 3.0
Exposed to Whole Body Vibration 3.0
Pace Determined by Speed of Equipment 3.0
Conflict Situations 2.8
Level of Competition 2.8
Deal With External Customers or the Public in General 2.8
Spend Time Kneeling, Crouching, Stooping, or Crawling 2.7

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.

Post-Baccalaureate Certificate 0.8%
Some College Courses 0.6%

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 4.0
Investigative 2.6
Enterprising 2.4

Interest areas

Physical/Manual Labor 6.4
Transportation/Machine Operation 4.8
Mechanics/Electronics 4.4
Nature/Outdoors 3.2
Engineering 2.3
Protective Service 1.6

Work styles

Dependability 3.0
Cautiousness 2.5
Attention to Detail 2.0
Stress Tolerance 2.0
Perseverance 1.8
Cooperation 1.7

Wages & employment

U.S. · annual wages (BLS OEWS)

$33k10th$38k25th$50kMedian$65k75th$82k90th
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.
32k202433k2034 (proj.)+2.3% · About average
Projected U.S. employment, 2024–2034 (BLS Employment Projections). A labor-market forecast for the occupation, not an AI-impact forecast.
10th percentile $33,350
25th percentile $38,450
Median (50th) $49,610
75th percentile $65,370
90th percentile $81,890
People employed 31,360

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
Transportation and Warehousing · Sector 22,880 $50,060
Construction · Sector 980 $41,710
Mining, Quarrying, and Oil and Gas Extraction · Sector 400 $60,610
Arts, Entertainment, and Recreation · Sector 390 $45,130
Professional, Scientific, and Technical Services · Sector 380 $61,720
Real Estate and Rental and Leasing · Sector 310 $37,600
Wholesale Trade · Sector 290 $61,480
Manufacturing · Sector 240 $54,500
Educational Services · Sector 90 $55,670
Accommodation and Food Services · Sector 30 $32,630
Engineering Services · National industry $61,720
Other Services (except Public Administration) · Sector $44,290

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
Transportation and Warehousing · Sector 15.22× 22,880
Mining, Quarrying, and Oil and Gas Extraction · Sector 3.43× 400
Arts, Entertainment, and Recreation · Sector 0.73× 390
Real Estate and Rental and Leasing · Sector 0.64× 310
Construction · Sector 0.59× 980
Wholesale Trade · Sector 0.24× 290
Professional, Scientific, and Technical Services · Sector 0.17× 380
Manufacturing · Sector 0.09× 240

Part of the Supply Chain & Transportation career cluster.

Exposure quadrant: AI task-overlap percentile vs Median pay Sailors and Marine Oilers sits at the 8th percentile of AI task-overlap and the 33rd percentile of median pay, placed here against 11 adjacent occupations on the same two axes. Lower overlap · higher pay Higher overlap · higher pay Higher overlap · lower pay Lower overlap · lower pay Sailors and Marine Oilers Dredge Operators Motorboat Operators Tank Car, Truck, and Ship Loaders Railroad Brake, Signal, and Switch Operators and Locomotive Firers Ship Engineers Riggers Captains, Mates, and Pilots of Water Vessels 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 Sailors and Marine Oilers — not advice or a forecast. Each is a real cross-link you can follow into the evidence.

Skills that travel

Capabilities this work builds that are used across many other occupations.

Paths in

How people typically prepare for this work.

Zoom out

On the global GenAI exposure gradient this work sits around the 15th percentile of 427 international occupations.

Write a report on thisheadline · factoids · citation

Sailors and Marine Oilers show 8th-percentile AI task overlap — and about 3,900 annual U.S. openings

  • Sailors and Marine Oilers rank in the 8th 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 3,900 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 about average (+2.3%) from 2024 to 2034.BLS Employment Projections 2024–34
  • Median annual pay is $49,610, across about 31,360 U.S. workers.BLS OEWS (May 2024)
Copy the whole kit
Sailors and Marine Oilers show 8th-percentile AI task overlap — and about 3,900 annual U.S. openings

• Sailors and Marine Oilers rank in the 8th 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 3,900 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 about average (+2.3%) from 2024 to 2034. (BLS Employment Projections 2024–34)
• Median annual pay is $49,610, across about 31,360 U.S. workers. (BLS OEWS (May 2024))

Source: Singulariki — "Sailors and Marine Oilers". https://singulariki.com/roles/role-53-5011-00
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. "Sailors and Marine Oilers." 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; AI Occupational Exposure (AIOE) Felten, Raj & Seamans; ILO / Gmyrek et al. GenAI exposure gradient 2025; IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022; Frey & Osborne (2013) frey-osborne-automation; Dingel & Neiman (2020) dingel-neiman-workathome. Accessed June 7, 2026. https://singulariki.com/roles/role-53-5011-00

APA

Singulariki. (2026). Sailors and Marine Oilers. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-53-5011-00

BibTeX
@misc{singulariki-role-53-5011-00,
  title  = {Sailors and Marine Oilers},
  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; AI Occupational Exposure (AIOE) Felten, Raj & Seamans; ILO / Gmyrek et al. GenAI exposure gradient 2025; IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022; Frey & Osborne (2013) frey-osborne-automation; Dingel & Neiman (2020) dingel-neiman-workathome. Accessed June 7, 2026},
  url    = {https://singulariki.com/roles/role-53-5011-00}
}

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

Embed this chart

Paste this into any page. It links back here for attribution.