What can I do with a degree in Mathematics?

Here below offers a selection of the destinations University of Exeter graduates from mathematics have gone on to. The information below is not exhaustive, however it does highlight the range of job and further study options available to you after your studies. 

If you wish to learn more about any of the jobs listed below you may wish to browse the job profiles on the Prospects website. 

Careers with a degree in Mathematics

Recent Exeter mathematics graduates have entered a wide range of careers. Some recent examples include:* (note most popular roles highlighted in bold)

Remember…

Many employers accept applications from graduates with any degree subject, so don't restrict your thinking to the jobs listed above. Use Prospects A-Z database of occupational profiles to find out more about the above roles. 

Other resources:

University of Exeter

UK resources

International resources

* Aggregated data taken from aggregating the responses from full-time, first degree, UK domiciled students who completed Graduate outcomes from 2017/18 to 2021/22 Graduate Outcomes surveys  

Employers of Exeter alumni with a degree in Mathematics

Recent Exeter mathematics graduates have entered a wide range of careers. Some recent examples include the following most popular destinations:* 

* Aggregated Data taken from aggregating the responses from full-time, first degree, UK domiciled students who completed Graduate outcomes from 2017/18 to 2021/22 Graduate Outcomes surveys.  

For more information on the above companies click here to access the University of Exeter Library research companies and organisations for your job search resource. See Career Zone Help withresearchingsectors and employers resource to aid research of the aforementioned employers. 

Skills

An Exeter mathematics degree will equip you with some great employability skills including: 

Soft/Transferable Skills

  • Abstract Thinking: handling of abstract ideas and manipulation of them effectively to develop new mathematical models and frameworks. 
  • Adaptability: adjustment to new situations and ready learning of new skills, embracing new mathematical concepts and applications. 
  • Attention to Detail: meticulous analysis of data, identification of patterns, and ensuring accuracy in mathematical work. 
  • Communication: clear explanation of mathematical concepts and reasoning, both verbally and in writing, to a variety of audiences. 
  • Critical Thinking: analysis of problems logically and systematically to identify underlying concepts and develop effective solutions. 
  • Lifelong Learning: a strong foundation and motivation for continuous learning, keeping up to date with advancements in the field of mathematics.  
  • Problem-Solving: breakdown of complex problems into manageable steps, application of relevant mathematical techniques, and evaluation of potential solutions. 
  • Self-Motivation: independent taking of initiative, setting of goals, and perseverance in learning and solving challenging problems. 
  • Teamwork: effective collaboration within teams, sharing of knowledge, and contribution to achieving common goals. 
  • Time Management: prioritisation of tasks, efficient management of workloads, and deadlines. 

Technical/Specialist Skills

  • Linear algebra: performance of operations on matrices, solving of systems of linear equations, understanding of vector spaces and linear transformations; essential for careers in data analysis, computer graphics and engineering. 
  • Calculus: utilisation of differential and integral calculus to analyse functions, optimise models, and calculate rates of change; instructive for applications in physics, engineering, economics and finance. 
  • Analysis: rigorous proof of mathematical statements, utilisation of concepts of real and complex analysis, understanding of convergence and continuity; fundamental for theoretical mathematics, research, and advanced scientific computing, key for careers in data science, actuarial science, market research and risk management. 
  • Probability and statistics: application of statistical methods to analyse data, model uncertainty, and draw informed conclusions from probabilistic models; vital for scientific computing, simulations and engineering design. 
  • Numerical analysis: use of computational techniques to solve complex mathematical problems, approximating solutions to equations and analysing numerical errors; essential for careers in finance, epidemiology, environmental science and operations research.
  • Modelling: development and analysis of mathematical models to represent real-world phenomena, understanding of model limitations and selecting appropriate techniques; valuable to process business problems in industries from finance to tech. 
  • Programming: proficiency in programming languages such as Python or MATLAB, allowing for automation of calculations and visualisation of data, highly valuable for data science, software development, scientific computing, and quantitative finance. 
  • Discrete mathematics: expertise in specialist functions such as graph theory or combinatorics, analysing discrete structures and their properties; essential for roles in computer science, cybersecurity, and algorithm development. 
  • Advanced mathematics: in-depth high-level numeracy in specific mathematical areas such as abstract algebra, differential geometry, or complex analysis, important for careers in computer science, cryptography, network analysis and optimisation, and emergent fields of quantum computing and artificial intelligence. 
  • Research skills: conducting independent research, critical evaluation of existing literature, and effective communication of research findings, essential for advanced research, academia, and specialised roles in consulting. 

Further Study

Around 24.6 % of mathematics graduates go on to pursue further study within 15 months of completing their undergraduate degree. Some recent progression routes include (note most popular roles highlighted in bold): 

Applied Mathematics, Modelling and Scientific Computing: 

  • MSc Applied Mathematics 
  • MSc Mathematical Modelling 
  • MSc Mathematical Modelling (Biology and Medicine) 
  • MSc Weather and Climate Science 

Data Science, Statistics, and Computing: 

  • MSc Advanced Computer Science 
  • MSc Advanced Computer Science with Business 
  • MSc Applied Data Science and Statistics 
  • MSc Computing 
  • MSc Cyber Security Analytics 
  • MSc Data Science 
  • MSc Data Science with Artificial Intelligence 
  • MSc Statistics

Finance, Economics, and Related Fields 

  • MSc Accounting and Finance
  • MSc Economics 
  • MSc Finance and Investment 
  • MSc Finance and Management 
  • MSc Financial Analysis and Fund Management 
  • MSc Financial Mathematics 
  • MSc Financial Technology (FinTech)    
  • MSc Investment and Finance (CFA Pathway) 

Other: 

  • MA Classics and Ancient History 
  • MPh Medical Studies 
  • MPh Complex Living Systems 
  • MPh Mathematics 
  • MSc Global Health Policy 
  • MSc Global Sustainability Solutions 

Pure/Theoretical Mathematics and Related Fields: 

  • MA Philosophy 
  • MPhil Physics/Engineering (CDT) 
  • MSc Advanced Mathematics 
  • MSc by Research in Physics 
  • MSc Mathematical Sciences 
  • MSc Mathematics 
  • PhD Chemistry 
  • PhD Mathematics 
  • PhD Oceanography 

Teaching and Education

  • PGCE in Primary with SEND 
  • PGCE Mathematics 
  • PGCE Mathematics Primary 
  • PGCE Secondary Mathematics 

Some sample University of Exeter postgraduate options: 

Useful resources: