Mathematics & Data Science BSc

Sabrina O'Neil
Oct 22
4 min read

Mathematics with Data Science combines the precision of mathematics with the practical power of data analysis. It teaches students how to collect, interpret, and apply data to solve real-world problems in technology, business, science, and society.

A BSc in Mathematics with Data Science blends theoretical maths with modern computing tools. Students learn how to model complex systems, analyse trends, and make evidence-based predictions — skills that are vital in today’s data-driven world.

Why Study Mathematics with Data Science?

There are many reasons why students choose to study this degree:

Data is shaping every industry, from healthcare and finance to gaming and climate science.
The course offers a balance between mathematical theory and hands-on computing.
Graduates are in high demand across both private and public sectors.
Students gain transferable skills in problem-solving, critical thinking, and analysis.
Opportunities for high-earning and flexible career paths, including remote work.

This degree suits students who enjoy problem-solving, logical thinking, and working with technology and numbers to understand real-world challenges.

Course Duration and Structure

In the UK, a BSc in Mathematics with Data Science typically takes three years of full-time study, or four years with a placement year, foundation year, or study abroad option.

A typical course structure includes:

Year 1: Core mathematics, statistics, and programming. Students learn fundamental concepts such as algebra, calculus, and coding in Python or R.

Year 2: Intermediate modules in data analysis, probability, linear algebra, and machine learning. Students start to apply mathematical methods to real data.

Year 3: Advanced modules in artificial intelligence, big data analytics, and statistical modelling. The final year often includes a research project or dissertation based on real-world data.

Many universities also include optional work placements or internships in technology, finance, or research sectors.

Entry Requirements

Entry requirements vary between universities but typically include one of the following:

A Levels: In Mathematics (and sometimes Further Mathematics, Physics, or Computer Science).
BTEC: A relevant Extended Diploma in Computing, Engineering, or Applied Science.
International Baccalaureate (IB): Including Mathematics and a science or technology subject.
Other qualifications: Access to Higher Education Diploma in Science, Mathematics, or Computing.
English language proficiency: Required for applicants whose first language is not English.
Strong mathematical ability and an interest in computing are key for success in this course.

Teaching and Assessment

Students learn through a combination of lectures, computer labs, tutorials, and practical workshops. The course often integrates real-world data projects and industry challenges.

Assessment methods include:

Coursework and data analysis projects
Programming assignments
Written exams
Group work and presentations
A final dissertation or applied research project

Teaching focuses on both theoretical understanding and practical data-handling experience.

Skills You Will Develop

A Mathematics with Data Science degree develops a strong set of analytical, computational, and professional skills, including:

Mathematical modelling and problem-solving
Statistical analysis and probability theory
Programming in Python, R, or MATLAB
Data visualisation and interpretation
Machine learning and predictive analytics
Logical and abstract reasoning
Communication and teamwork
Research and report writing

These skills are highly sought after across technology, finance, and research industries.

Career Prospects

Graduates are well-prepared for roles across technology, science, and business sectors.

Typical career paths include:

Data analyst or data scientist
Statistician or quantitative analyst
Machine learning engineer
Software developer or systems analyst
Financial or business analyst
Risk modeller or actuary
Research scientist or academic
Further study in applied mathematics, computer science, or artificial intelligence
Employers include technology companies, banks, research institutes, healthcare organisations, and government departments.

Tips for Prospective Students

Strengthen your skills in mathematics and basic coding before the course.
Explore free online data projects and challenges (e.g. Kaggle, DataCamp).
Stay up to date with data trends, AI, and analytics technologies.
Develop your communication skills to explain complex data clearly.
Gain experience through internships or part-time data analysis projects.
Join professional organisations such as the Royal Statistical Society (RSS) or Institute of Mathematics and its Applications (IMA).

Course Variations

Universities offer several related degrees, including:

Mathematics with Data Science (BSc): Core focus on mathematical and data analysis skills.

Mathematics and Statistics (BSc): Emphasising probability, modelling, and statistical methods.

Computer Science with Data Analytics (BSc): Exploring programming and large-scale data systems.

Data Science (BSc): Focusing on machine learning, data management, and visualisation.

Applied Mathematics (BSc): Concentrating on mathematical theory and its real-world applications.

Artificial Intelligence and Data Science (BSc): Combining AI algorithms and predictive modelling.