Mathematician
Snapshot
Mathematicians study and deepen existing mathematical theories in order to expand the knowledge and find new paradigms within the field. They can apply this knowledge to challenges presented in engineering and scientific projects in order to assure that measurements, quantities, and mathematic laws prove their viability.
Mathematicians are at the forefront of mathematical discovery, constantly seeking to refine existing theories and uncover new paradigms. Your days might involve rigorous research, developing new mathematical models, or applying these models to practical challenges in fields like engineering, physics, computer science, and finance. You'll be expected to critically evaluate data, ensure the accuracy of measurements, and validate mathematical laws to guarantee their reliability.
- • Conducting original research to expand mathematical knowledge.
- • Developing and applying mathematical models to solve complex problems.
- • Analyzing data and ensuring the accuracy of calculations and measurements.
Where this occupation is in demand
Reported labour shortages and surpluses, by year. Published for occupation groups, not for individual job titles.
Deeper colour: reported the same way in more consecutive years.
Figures cover Science and engineering professionals — 274 jobs including this one.
In shortage: Denmark, Italy, Luxembourg, Netherlands.
Longest-running shortage: Luxembourg, 3 years.
Where it is regulated, your qualification would need formal recognition before you could practise.
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.
Explore More
Find your career path and explore the science behind our recommendations.
Could mathematician fit you?
Answer three quick questions. This is not a full assessment — it is a teaser to help you decide whether to compare your profile.
Do you enjoy tasks that require Analytical Thinking?
Do you enjoy tasks that require Attention to Detail?
Do you enjoy tasks that require Persistence?
Future Outlook for mathematician
The outlook for mathematician 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 mathematician 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.
How AI may change this role
Deterministic, model-based interpretation of current role signals — not a guarantee of replacement.
What still depends on people
- interact professionally in research and professional environments
- evaluate research activities
- manage intellectual property rights
Where AI may become a co-pilot
- manage open publications
- demonstrate disciplinary expertise
- manage findable accessible interoperable and reusable data
Tasks most exposed to automation
- synthesise information
- apply for research funding
- execute analytical mathematical calculations
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 workflow automation, decision-support software, and process digitisation
Exposure to physical automation, robotics, and sensor-driven task displacement
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
Digital Technology
A typical day as a mathematician
09 09:00 · Morning apply for research funding
10 10:30 · Mid-morning apply research ethics and scientific integrity principles in research activities
12 12:00 · Midday manage intellectual property rights
14 14:00 · Afternoon operate open source software
15 15:30 · Late afternoon apply scientific methods
17 17:00 · Wrap-up communicate mathematical information
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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manage findable accessible interoperable and reusable data
Produce, describe, store, preserve and (re) use scientific data based on FAIR (Findable, Accessible, Interoperable, and Reusable) principles, making data as open as possible, and as closed as necessary.
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perform scientific research
Gain, correct or improve knowledge about phenomena by using scientific methods and techniques, based on empirical or measurable observations.
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apply scientific methods
Apply scientific methods and techniques to investigate phenomena, by acquiring new knowledge or correcting and integrating previous knowledge.
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conduct quantitative research
Execute a systematic empirical investigation of observable phenomena via statistical, mathematical or computational techniques.
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apply research ethics and scientific integrity principles in research activities
Apply fundamental ethical principles and legislation to scientific research, including issues of research integrity. Perform, review, or report research avoiding misconducts such as fabrication, falsification, and plagiarism.
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promote open innovation in research
Apply techniques, models, methods and strategies which contribute to the promotion of steps towards innovation through collaboration with people and organizations outside the organisation.
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integrate gender dimension in research
Take into account in the whole research process the biological characteristics and the evolving social and cultural features of women and men (gender).
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study the relationships between quantities
Use numbers and symbols to research the link between quantities, magnitudes, and forms.
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conduct research across disciplines
Work and use research findings and data across disciplinary and/or functional boundaries.
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promote the participation of citizens in scientific and research activities
Engage citizens in scientific and research activities and promote their contribution in terms of knowledge, time or resources invested.
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draft scientific or academic papers and technical documentation
Draft and edit scientific, academic or technical texts on different subjects.
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disseminate results to the scientific community
Publicly disclose scientific results by any appropriate means, including conferences, workshops, colloquia and scientific publications.
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publish academic research
Conduct academic research, in universities and research institutions, or on a personal account, publish it in books or academic journals with the aim of contributing to a field of expertise and achieving personal academic accreditation.
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write scientific publications
Present the hypothesis, findings, and conclusions of your scientific research in your field of expertise in a professional publication.
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communicate mathematical information
Use mathematical symbols, language and tools to present information, ideas and processes.
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communicate with a non-scientific audience
Communicate about scientific findings to a non-scientific audience, including the general public. Tailor the communication of scientific concepts, debates, findings to the audience, using a variety of methods for different target groups, including visual presentations.
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create solutions to problems
Solve problems which arise in planning, prioritising, organising, directing/facilitating action and evaluating performance. Use systematic processes of collecting, analysing, and synthesising information to evaluate current practice and generate new understandings about practice.
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manage research data
Produce and analyse scientific data originating from qualitative and quantitative research methods. Store and maintain the data in research databases. Support the re-use of scientific data and be familiar with open data management principles.
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interact professionally in research and professional environments
Show consideration to others as well as collegiality. Listen, give and receive feedback and respond perceptively to others, also involving staff supervision and leadership in a professional setting.
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operate open source software
Operate Open Source software, knowing the main Open Source models, licensing schemes, and the coding practices commonly adopted in the production of Open Source software.
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speak different languages
Master foreign languages to be able to communicate in one or more foreign languages.
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execute analytical mathematical calculations
Apply mathematical methods and make use of calculation technologies in order to perform analyses and devise solutions to specific problems.
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evaluate research activities
Review proposals, progress, impact and outcomes of peer researchers, including through open peer review.
mathematical economics
The interdisciplinary field between mathematical methods and economics that deals with using math principles to contruct models for economic theory where conclusions can be drawn following a mathematical logic.
mathematical physics
The interdisciplinary field between mathematics and physics that deals with the mathematical foundations of theoretical physics. It addresses issues in quantum mechanics and atomic and molecular physics.
- algebra
- mathematical modelling
- mathematics
- Monte Carlo simulation
- numerical sequences
- scientific modelling
- scientific research methodology
- statistics
See whether this role fits your Career DNA
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Scan to continue on mobilePath to become a mathematician
What it typically takes to qualify: education level, where it is a regulated profession, and where to study.
Bachelor's or equivalent level
Regulated in 8 countries on record. Minimum EQF 6–7, depending on the country.
Reflects the EU regulated-professions database. Not legal advice — confirm requirements with the relevant national authority before relying on this for a career or immigration decision.
Real programmes leading to this occupation, by country.
Growth Pathways & Similar Roles
Explore typical career progression paths, adjacent skills, and similar roles to plan your next transition.
Where does mathematician fit?
Similarity scores based on skill overlap from ESCO data.
Frequently asked questions
- What kind of projects might a mathematician work on?
- Mathematicians contribute to a wide range of projects. This could include developing algorithms for data analysis, creating models for financial risk assessment, optimizing engineering designs, or contributing to advancements in cryptography and cybersecurity.
- What skills are essential for success as a mathematician?
- Strong analytical and problem-solving skills are paramount. You'll also need excellent abstract reasoning abilities, a deep understanding of mathematical principles, and the ability to communicate complex ideas clearly and concisely, both verbally and in writing.
- Is a PhD always required to become a mathematician?
- While a PhD is often necessary for research-focused roles and academic positions, some applied mathematics positions in industry may be accessible with a strong Master's degree and relevant experience. However, advanced roles and leadership positions typically require doctoral-level qualifications.
- Is there a shortage of Mathematician in Europe?
- No. In the 2025 ELA/EURES edition, a surplus was reported in 6 of the 9 European countries that assessed this occupation group: Austria, Bulgaria, Germany, Greece and 2 more. 3 countries reported a shortage. These assessments are published per occupation group rather than per job title.
- How much does Mathematician pay in the United States?
- $121,680 a year at the median, as of 2025-05. State medians run from $65,510 to $162,280. Source: US Bureau of Labor Statistics. This is a United States figure and not a projection for Europe.
- Is Mathematician a regulated profession?
- It is listed as a regulated profession in 8 European countries: Spain, Sweden, Poland, Denmark and 4 more. The lowest qualification level required among them is EQF 6. Where a profession is regulated, a qualification earned elsewhere has to be formally recognised before you can practise. Source: EU Regulated Professions Database.
Sources: ESCO O*NET ELA/EURES Cedefop BLS Data updated September 20, 2026 About our data