MSc Mathematics and Data Science

1 Year On Campus Masters Program

University of Stirling

Program Overview

If you’re excited about combining the power of mathematics with cutting-edge data science skills, the MSc Mathematics and Data Science at the University of Stirling equips you with the practical expertise that employers in today’s data-driven world are looking for. You’ll master advanced analytical methods, programming in languages like Python, R and MATLAB, and apply your learning to real-world problems through industry-linked projects and a research-focused summer project.

Curriculum structure

Autumn & Spring Terms:
In your first semesters, you’ll build a solid grounding in the mathematical principles behind data science and learn to work with large datasets using both theory and practice. You’ll engage with core topics such as statistical analysis of large datasets and network data, basic and advanced programming with R, MATLAB and Python, and probability, stochastic optimisation and artificial intelligence, equipping you with the skills to model, analyse and interpret complex data. These taught components are reinforced with small-group discussions and practical sessions so you can immediately apply what you learn to real problems.

Industry Projects & Applications:
Alongside your core learning, you’ll have the chance to collaborate on commercially relevant projects with industry partners such as NatWest, Scottish National Investment Bank and SportScotland, bringing your mathematical modelling and data science skills to bear on real business challenges — from forecasting market imbalances to analysing sports performance data. This industry engagement helps you build practical experience and professional contacts while you study.

Summer Research Project:
In the summer, you’ll complete a research or data analysis project of your choice, applying your mathematical and computational skills to investigate a real-world dataset or system. This final piece not only showcases your capability to integrate theory and practice but also strengthens your portfolio for employers or further study.

Focus areas

Statistical analysis of large and networked data, mathematical modelling, machine learning, programming with Python/R/MATLAB, probability and stochastic optimisation, relational and non-relational databases, cluster computing.

Learning outcomes

You will graduate with advanced mathematical understanding, practical data science skills, experience in programming and analytics, the ability to solve complex real-world problems, and confidence in applying research and modelling techniques to industry challenges.

Professional alignment (accreditation)

This degree is shaped around the real demands of the data industry and supported by strong connections with The Data Lab innovation centre, giving you networking opportunities and insights into current industry practice.

Reputation (employability rankings)

The University of Stirling is ranked among the Top 3 in Scotland and Top 20 in the UK for Mathematics in the National Student Survey 2024, recognised for quality teaching, strong student satisfaction and excellent preparation for careers in data and analytics.

Experiential Learning (Research, Projects, Internships etc.)

When you study the Mathematics and Data Science MSc at the University of Stirling, you’re stepping into a programme where practical skills are at the heart of learning. You’ll work directly with academic staff on commercially relevant research projects tackling real data problems such as forecasting market imbalances, analysing sports performance data, or exploring natural language patterns the kind of work that mirrors what professional data scientists do every day. You’ll also build strong programming and analytical skills through hands-on experience with industry-standard software, learn to design mathematical models of real systems, and engage with guest speakers from leading tech and data organisations all while supported by a research-active department linked with Scotland’s data science innovation community. This means you won’t just learn concepts you’ll use them in meaningful, practical contexts that boost your confidence and readiness for a data-centred career.

Experiential Learning Opportunities and Tools:

Real data projects with industry relevance: You’ll work on live or past projects based with organisations such as Intergen, NatWest, SportScotland Institute of Sport, BBC World Service and Scottish National Investment Bank, gaining experience with data sets, forecasting, and machine-learning tasks that matter to employers.
Extensive programming experience: The programme includes practical training in Python, R and MATLAB all widely used in data science and analytics roles so you graduate job-ready with coding skills embedded in your workflow.
Mathematical modelling and analysis: You’ll apply mathematical principles to build and analyse models of real-world systems, gaining valuable skills in stochastic optimisation, probability, AI techniques and statistical analysis that are essential in modern data work.
Industry engagement and networking: With strong ties to The Data Lab innovation centre and a programme of guest industry speakers (including representatives from Huawei, SkyScanner and HSBC), you’ll get insight into current professional practices and networking opportunities.
Small-group sessions and practical classes: In addition to lectures, you’ll take part in discussion groups and practical sessions where you can ask questions, practise new techniques, and collaborate with peers a key part of experiential learning.
Summer research project: During the summer period you’ll complete a research or applied data science project of your choice, often based around a real data set or model, demonstrating your ability to use your skills in an independently driven context.
Collaborative research environment: The Department of Computing Science and Mathematics actively engages in interdisciplinary research in data science and intelligent systems, giving you a chance to connect with research groups working on contemporary challenges.
Computing and data facilities: The university’s mathematics computing labs and digital learning platforms support your work with datasets, simulation tools and collaborative software — essential for real-world analytics tasks.

Progression & Future Opportunities

Graduates from the MSc Mathematics and Data Science at the University of Stirling are equipped with highly desirable analytical, programming and data-driven modelling skills that employers are actively seeking: typical job roles include Data Scientist, Data Analyst, Business Analyst and Quantitative Model Risk Analyst with opportunities across finance, technology, healthcare, government and environmental sectors. The blend of mathematics with real-world data science experience helps you move straight into impactful careers or set you up for further academic research.

Here’s how this programme supports your progression & future opportunities:

University services that help students to employ:
• You’ll benefit from Stirling’s careers support and networking events, including guest lectures and industry engagement opportunities with companies like Huawei, SkyScanner, HSBC and others — helping you build professional contacts.
• The university’s strong links with The Data Lab innovation centre give you access to data science networking, industry insight and support that can lead to employment or project collaborations. Employment stats and salary figures:
• Data analyst and data science roles are ranked among the top 10 fastest-growing global jobs, reflecting demand for the skills you’ll develop.
• In the UK, the average salary for mathematics and data science professionals is around £46,792 per year, with entry-level starting roles at about £38,383 and experienced professionals earning up to around £58,949.
University–industry partnerships (specific):
• The programme includes commercially relevant industry projects with organisations such as NatWest, Scottish National Investment Bank, SportScotland Institute of Sport, BBC World Service and more — giving you hands-on experience solving real data problems.
• You’ll engage with local and national industry professionals through seminars and events, building real insight into employer expectations.
Long-term accreditation value:
• The University of Stirling’s Mathematics provision is ranked top 5 in Scotland and top 20 in the UK, enhancing your degree’s international recognition and credibility with employers.
• The blend of mathematical theory and practical data science tools (Python, R, machine learning, stochastic modelling) equips you with transferable skills valued across many sectors.
Graduation outcomes:
• Graduates move into roles such as Data Scientist, Data Analyst, Business Analyst, Quantitative Model Risk Analyst and Researcher; past alumni have been employed by TSB Bank, UST, the Scottish Government and Aberdeen Group, among others.
• The degree also opens opportunities in sectors like healthcare, sport analytics, environmental services and start-ups, reflecting its broad application.

Further Academic Progression:
After completing the MSc, you’ll be well-placed to progress into PhD or MPhil research in Data Science, Mathematics, Artificial Intelligence or related fields, building on your research project experience and industry collaborations. The university’s research community and ties to organisations like The Data Lab provide excellent support for advanced study and research careers.