Predictive Maintenance Expert
Key facts
Predictive maintenance experts analyse data collected from sensors located in factories, machineries, cars, railroads and others to monitor their conditions in order to keep users informed and eventually notify the need to perform maintenance.
Predictive maintenance experts play a crucial role in ensuring the reliability and efficiency of machinery and equipment. Your day might involve analyzing sensor data from factories, vehicles, or infrastructure, identifying patterns that indicate potential issues, and recommending proactive maintenance strategies. This role combines technical skills with analytical thinking to improve operational performance and reduce unexpected breakdowns.
- • Analyze data streams from sensors and equipment to identify anomalies and predict failures.
- • Develop and implement predictive maintenance models and algorithms.
- • Collaborate with maintenance teams to schedule and prioritize maintenance activities.
Where this occupation is in demand
Reported labour shortages and surpluses, by year. Published for occupation groups, not for individual job titles.
Figures cover Science and engineering professionals — 274 jobs including this one.
In shortage: Austria, Belgium, Bulgaria, Cyprus and 7 more.
Longest-running shortage: Netherlands, 4 years.
Select a place on the map to see its figures.
About this source›
Source: ELA/EURES labour shortages and surpluses. Readings are published at occupation-group level, and cover Europe. Editions differ in annex layout and country coverage, so a change between years does not always mean the labour market changed. Countries in grey were not reported, which is not the same as being in balance.
What these words mean
The four things this section reports
- Reported demand
- Whether employers report needing people in this job — a judgement published by a national or EU body, not a count.
- Where it is heading
- Which way employment in this job is expected to move over the coming years, from an official projection.
- Openings
- Roughly how many openings arise — from growth and from people leaving the job.
- Typical pay
- What people in this job typically earn where the source publishes it. Blank does not mean unpaid; it means nobody publishes it for that place.
A measure is left out when nobody publishes it for that place, rather than shown as zero.
Which way the market leans for you
- In your favour
- More openings than people looking — employers are competing for candidates.
- Balanced
- Openings and candidates are roughly matched.
- Competitive
- More people looking than openings — expect to compete.
- Mixed evidence
- Sources disagree, or the same occupation group is short in one part and oversupplied in another.
Every source resolves to one of these four, so there is a single vocabulary to learn. What differs is the evidence behind it, which is printed underneath each verdict — a measured ratio of openings to jobseekers, or an assessment published by a national body.
How this job compares with other jobs in the same country
- Strong
- Among the strongest in that country
- Good
- Stronger than most jobs in that country
- Mixed
- About typical for that country
- Weak
- Weaker than most jobs in that country
This is a rank within one country, not a score you can carry across borders — the registers behind two countries count different people, so the same number means different things in each. It is also why a job can be among the strongest in a country and still show as Competitive: it leads the field in a market that is crowded overall.
Where these come from
Every figure is published by a national statistics office, a public employment service or an EU body, and each card names its source and the period it covers. Some places are counted monthly, others assessed once or twice a year, so two places on the same map can be describing different moments — the date is always shown.
None of this predicts one person’s chances. It describes a market.
Reported demand · Typical pay · Where it is heading (United States, Ireland, Australia, Malta, United Kingdom)
| Reported demand | Typical pay | Where it is heading | |
|---|---|---|---|
| United States | Not reported | $130,220 2025-05 | +6.2% 2024–2034 · BLS 2024-2034 |
| Ireland | Not reported | — | +35.5% 2023–2035 · Cedefop 2026 * |
| Australia | Shortage reported Jobs and Skills Australia 2025 * | — | — |
| Malta | Surplus reported ELA/EURES 2024 * | — | — |
| United Kingdom | Not reported | £37,991 2025-provisional | — |
* Published for occupation groups, not for individual job titles.
U.S. Bureau of Labor Statistics (OEWS)
Source: Office for National Statistics, Annual Survey of Hours and Earnings, Open Government Licence v3.0
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Future Outlook for predictive maintenance expert
The outlook for predictive maintenance expert reflects a balanced mix of automation exposure and durable, human-led work.
How are these scores calculated?
The Resilience Score (0–100) estimates how structurally protected this occupation is from automation and AI disruption, based on task-level analysis. Higher scores mean more human-judgment-intensive tasks. AI Exposure shows the estimated percentage of task hours that current AI capabilities could affect. These are model-derived structural indicators, not predictions about individual job security.
How could predictive maintenance expert change as AI adoption grows?
This role is likely to change gradually, with AI supporting selected tasks rather than replacing the whole occupation.
Illustrative scenario based on task automatability — not a forecast. Values are rounded the further ahead you look.
This role is likely to change gradually, with AI supporting selected tasks rather than replacing the whole occupation.
Illustrative scenario based on task automatability — not a forecast. Values are rounded the further ahead you look.
Model-based estimate. Use it as a planning signal, not a guarantee.
Compare this to your profile
How AI may change this role
Deterministic, model-based interpretation of current role signals — not a guarantee of replacement.
What still depends on people
- apply information security policies
- advise on equipment maintenance
- test sensors
Where AI may become a co-pilot
- apply statistical analysis techniques
- analyse big data
- develop data processing applications
Tasks most exposed to automation
- gather data
- perform data analysis
- manage data
Vital Signs & AI Vectors
AI Exposure Vectors
0-100%Exposure to AI-assisted analysis, pattern recognition, and predictive modelling tasks
Exposure to content generation, creative augmentation, and large language model tools
Exposure to physical automation, robotics, and sensor-driven task displacement
Exposure to workflow automation, decision-support software, and process digitisation
Technical Details
NexFuture v3.0 estimates automation exposure natively from ESCO essential-skill groups, weighted by skill mass and calibrated against expert anchors. Scores are probabilistic estimates, not guarantees. See the NexFuture Methodology White Paper for full details.
Measures automation exposure. It does not measure pay, demand, or how many jobs exist near you.
What people in this role usually do
Supply Chain & Transportation
A typical day as a predictive maintenance expert
09 09:00 · Morning develop data processing applications
10 10:30 · Mid-morning apply information security policies
12 12:00 · Midday design sensors
14 14:00 · Afternoon manage data
15 15:30 · Late afternoon model sensor
17 17:00 · Wrap-up advise on equipment maintenance
Task order is illustrative. Individual days vary.
What you need to do this work
The skills, knowledge and tools this role calls for — and the traits and rewards that come with it.
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apply statistical analysis techniques
Use models (descriptive or inferential statistics) and techniques (data mining or machine learning) for statistical analysis and ICT tools to analyse data, uncover correlations and forecast trends.
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analyse big data
Collect and evaluate numerical data in large quantities, especially for the purpose of identifying patterns between the data.
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design sensors
Design and develop different types of sensors according to specifications, such as vibration sensors, heat sensors, optical sensors, humidity sensors, and electric current sensors.
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model sensor
Model and simulate sensors, products using sensors, and sensor components using technical design software. This way the viability of the product can be assessed and the physical parameters can be examined before the actual building of the product.
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gather data
Extract exportable data from multiple sources.
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perform data analysis
Collect data and statistics to test and evaluate in order to generate assertions and pattern predictions, with the aim of discovering useful information in a decision-making process.
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advise on equipment maintenance
Advise customers on the appropriate products, methods and, if necessary, interventions to ensure proper maintenance and prevent premature damage of an object or an installation.
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test sensors
Test sensors using appropriate equipment. Gather and analyse data. Monitor and evaluate system performance and take action if needed.
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apply information security policies
Implement policies, methods and regulations for data and information security in order to respect confidentiality, integrity and availability principles.
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manage data
Administer all types of data resources through their lifecycle by performing data profiling, parsing, standardisation, identity resolution, cleansing, enhancement and auditing. Ensure the data is fit for purpose, using specialised ICT tools to fulfil the data quality criteria.
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ensure equipment maintenance
Ensure that the equipment required for operations is regularly checked for faults, that routine maintenance tasks are performed, and that repairs are scheduled and performed in the case of damage or flaws.
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develop data processing applications
Create a customised software for processing data by selecting and using the appropriate computer programming language in order for an ICT system to produce demanded output based on expected input.
automotive diagnostic equipment
The equipment used to examine automotive systems and components.
- computer programming
- electrical engineering
- electricity
- electronics
- ICT networking hardware
- mathematics
- statistics
- computer simulation
Path to become a predictive maintenance expert
What it typically takes to qualify: education level, where it is a regulated profession, and where to study.
Bachelor's or equivalent level
212 programmes in 21 countries teach the core skills of this job. Plus 147 short courses that build single skills.
A few examples, taught in the language of this page:
These are 6 of 359.
Sources
- 1. Source: Commonwealth of Australia (Department of Education), CRICOS, data.gov.au, CC BY 2.5 AU. Data as at 01/09/2026. Adapted by NexPath.
- 2. Source: Study with New Zealand (studywithnewzealand.govt.nz), Education New Zealand. Copyright in the material is owned by Education New Zealand (All content (c) Education New Zealand). Listings are provided by the education providers, are for information and promotional purposes only, and are not endorsed by Education New Zealand; each provider is responsible for its own content.
- 3. Source: Europass Qualification Dataset Register (European Commission)
- 4. Source: Malta Qualifications Registry, Malta Further and Higher Education Authority (qualifications.mfhea.gov.mt).
- 5. Source: Study in Korea, National Institute for International Education (NIIED) (studyinkorea.go.kr).
Growth Pathways & Similar Roles
Explore typical career progression paths, adjacent skills, and similar roles to plan your next transition.
Where does predictive maintenance expert fit?
Similarity scores based on skill overlap from ESCO data.
For organisations
The data on this page, working for your students, clients and staff.
Frequently asked questions
What kind of industries employ predictive maintenance experts?
What skills are most important for success in this role?
How does this role differ from traditional preventative maintenance?
How much does Predictive Maintenance Expert pay in the United States?
Sources: ESCO O*NET ELA/EURES Cedefop BLS Data updated October 3, 2026 About our data