BSc in Mathematics with Statistics

4 Years On Campus Bachelors Program

Heriot Watt University Edinburgh

Program Overview

The BSc (Hons) Mathematics with Statistics at Heriot-Watt gives you a powerful combination of rigorous mathematical training and modern statistical techniques, ideal if you enjoy analytical thinking and working with data. This degree prepares you for high-demand careers in data science, finance, analytics, research, and technology by equipping you with strong theoretical foundations and practical modelling skills.

Curriculum Structure

Year 1

Your first year introduces you to the core of university mathematics through courses such as Calculus A/B, Introduction to University Mathematics, and Elements of Probability. You also begin building statistical intuition with modules like Problem Solving and Topics in Statistical Practice, giving you early exposure to real data and analytical reasoning.

Year 2

In second year, you deepen your mathematical toolkit with Real Analysis, Linear Algebra, Multivariable Calculus, and Numerical Analysis A. At the same time, you develop a solid grounding in statistical theory through Probability and Statistics A and Probability and Statistics B, strengthening your understanding of data distributions, uncertainty, and inference.

Year 3

Third year moves into more advanced material, including Abstract Algebra, Vector Analysis, Complex Analysis, and Ordinary Differential Equations. You also explore specialist areas in statistics through Statistical Models A and Statistical Models B, and you can tailor your degree further with options such as Further Statistical Methods or Applied Mathematics B, depending on whether you prefer theoretical or practical applications.

Year 4 (Honours Year)

Your final year combines advanced mathematics with specialised statistical pathways. You study core topics such as Stochastic Processes and then select from high-level options like Bayesian Inference, Computational Methods, Time Series and Machine Learning, Optimisation, Topology, or Partial Differential Equations. You also complete an independent research-based project, demonstrating your ability to work with complex mathematical or statistical problems.

Focus Areas

Pure and applied mathematics, probability theory, statistical modelling, numerical analysis, stochastic processes, Bayesian inference, data analysis, optimisation, and mathematical methods for real-world applications.

Learning Outcomes

You will develop deep mathematical understanding, strong logical and analytical reasoning, and the ability to apply statistical and computational techniques to complex, data-driven problems. Graduates leave with the versatility to work in data science, finance, analytics, research, engineering, and other quantitative industries.

Professional Alignment (Accreditation)

While not tied to a specific professional accreditation body, this degree aligns closely with pathways in data science, quantitative finance, actuarial support roles, research, and postgraduate study in mathematics, statistics, and data-driven disciplines.

Reputation (Employability Rankings)

Heriot-Watt is consistently recognised for excellent graduate outcomes, ranking among the top UK universities for employability and graduate prospects. Mathematics graduates from the university regularly move into competitive roles across finance, professional services, analytics, engineering, and technology-driven sectors.

Experiential Learning (Research, Projects, Internships etc.)

Students in this programme gain strong practical skills by combining mathematics with modern statistical methods and computational tools. From day one, you learn how to model real-world problems, analyse data, and apply theory to practice. The curriculum balances rigorous mathematics with applied statistics, enabling you to work with data sets, simulations, and computational models. Group projects, workshops, and supervised assignments ensure you graduate with hands-on experience and ready-to-use problem-solving skills.

You’ll also benefit from research-focused teaching, access to specialised facilities, and opportunities to collaborate with peers, preparing you for careers in data science, finance, analytics, research, and more.

Here’s how experiential learning is built into the programme:

Experiential Learning Highlights:

Integrated mathematics and statistics teaching: Core modules in mathematics (linear algebra, analysis, differential equations) are paired with statistics (probability, statistical modelling, applied methods) throughout the programme.
Computational and programming tools: Students learn and use software such as MATLAB, Python, and statistical packages for data analysis, modelling, and simulation.
Group projects and collaborative problem-solving: Many modules include team-based assignments, collaborative workshops, and data-driven challenges to develop communication and teamwork skills.
Final-year research project: Students complete a supervised dissertation, applying advanced mathematics and statistics to real or theoretical problems.
Access to world-class mathematics and statistics communities: Exposure to Heriot-Watt’s research culture and institutes ensures you learn from current research and up-to-date statistical methods.
Peer support and mentoring (“Maths Café”): Peer-led support sessions help students tackle challenging topics, collaborate on problems, and refine analytical thinking.
Modern library and digital resources: Dedicated resources for mathematics and statistics, including textbooks, journals, databases, and quiet study areas.
Industry-relevant skills: Emphasis on data interpretation, statistical modelling, computational analysis, and presentation skills ensures you are prepared for a variety of careers requiring quantitative expertise.

Who this programme suits

Ideal for students who enjoy both abstract mathematics and working with data.
Suitable for careers in data science, finance, analytics, actuarial science, research, or technology-driven fields.
Provides a strong foundation for postgraduate study or flexible career options that demand high-level quantitative and problem-solving skills.

Why Heriot-Watt University stands out

Mathematics and statistics degrees at Heriot-Watt are highly regarded, with strong graduate employment outcomes across multiple sectors.
The programme combines academic rigor with practical training, collaborative learning, and research-focused teaching.
Students gain a wide skillset, including pure and applied mathematics, statistics, and computational techniques, making them versatile and industry-ready.

Progression & Future Opportunities

Graduates of Mathematics with Statistics from Heriot-Watt leave equipped with strong analytical, statistical, and problem-solving skills — qualities highly sought after across finance, data science, technology, and research sectors. Most students secure professional roles or advance to further study soon after graduation, reflecting the programme’s strong reputation and industry relevance.

Typical job roles include:

Data Scientist / Data Analyst
Quantitative / Risk Analyst
Software Developer / Technical Consultant
Research or Statistical Consultant

University support for employability:

Careers and Graduate Futures Service: personalised career guidance, CV support, and interview coaching for STEM students.
Maths Café: peer-supported initiative for academic help, skill building, and confidence in problem-solving and communication.
Go Global mobility opportunities: study abroad at Heriot-Watt’s international campuses to gain global experience and connections.

Employment statistics & salary outcomes:

Around 80% of graduates are in professional employment within 15 months of finishing the degree.
Average starting salary is approximately £28,000, with many graduates’ earnings increasing over the following years.
Graduates enter sectors such as finance, business analytics, IT, data science, consultancy, and education.

Industry relevance & long-term value:

The degree combines mathematics with applied statistics, preparing students for roles in finance, technology, research, and business analytics.
The programme’s reputation in mathematics ensures strong credibility with employers in both the UK and internationally.
Curriculum includes modern statistical modelling, probability, analysis, and computational skills, which remain valuable as industries evolve.

Graduation outcomes:
Students gain a versatile skill set: advanced mathematics, statistical reasoning, analytical thinking, and computational proficiency. These skills equip graduates for technical, research, and quantitative careers worldwide.

Further Academic Progression:

After completing the degree, students can pursue a variety of postgraduate pathways:

Master’s degrees in Statistics, Data Science, Applied Mathematics, Quantitative Finance, or Computational Modelling.
MSc or PhD in mathematical sciences or related disciplines for those interested in research or academia.
Career-oriented progression into interdisciplinary areas such as data science, machine learning, actuarial science, finance, and analytics.