BSc in Mathematics and Statistics and Op Research

3 Years On Campus Bachelors Program

Queens University Belfast

Program Overview

The BSc in Mathematics and Statistics and Operational Research at Queen’s University Belfast is a three‑year undergraduate degree that combines strong analytical mathematics with practical statistical analysis and operational research methods to solve complex, real‑world problems. It suits students who enjoy quantitative reasoning, data interpretation, and developing solutions that inform decisions in science, business, and industry.

Curriculum Structure

Year 1
In the first year, students establish essential mathematical and statistical foundations through modules such as Introduction to Algebra and Analysis and Introduction to Probability & Statistics, which build core skills in calculus, algebraic reasoning, and data interpretation. Complementing this are modules like Mathematical Reasoning to hone logical analytical skills and Algorithmic Thinking to introduce basic programming and computational approaches to mathematical problems.

Year 2
The second year deepens students’ statistical and mathematical understanding with modules such as Statistical Inference, strengthening rigorous analysis of data and statistical models, and Metric Spaces, which extends abstract mathematical thinking. Students also explore Methods of Operational Research as an optional module, where they learn to formulate and solve optimisation and decision problems, applying mathematics to real‑life operational contexts.

Year 3
In the final year, students engage with advanced and applied topics including Statistical Data Mining with Machine Learning to explore modern data analysis techniques, and Mathematical Investigations, where they tackle open‑ended problems with independent and group research. A substantial Statistics Project further enables students to design and conduct a significant investigation, applying statistical packages and analytical tools to interpret complex data and present their findings professionally.

Focus Areas
Mathematical analysis, probability and statistics, statistical modelling, data mining and machine learning concepts, operational research techniques, mathematical reasoning and investigation.

Learning Outcomes
Students will be able to apply mathematical and statistical methods to real‑world problems, use computational tools and software for quantitative analysis, formulate logical arguments and solutions, interpret and present data with clarity, and conduct independent research projects demonstrating analytical depth.

Professional Alignment (Accreditation)
The degree is awarded by Queen’s University Belfast and aligns with UK quality assurance standards, giving graduates a qualification recognised by employers in sectors such as finance, analytics, consulting, science, and government where quantitative and data skills are in high demand.

Reputation (Employability Rankings)
Queen’s University Belfast is part of the Russell Group of research‑intensive UK universities, known for its strong international reputation in mathematics, statistics, and science education, and its graduates consistently achieve strong employability outcomes with opportunities in industry and further research pathways.

Experiential Learning (Research, Projects, Internships etc.)

The BSc in Mathematics and Statistics & Operational Research at Queen’s University Belfast brings mathematical thinking to life with practical experience rooted in real‑world analysis and problem solving. Students learn in the School of Mathematics and Physics’ dedicated teaching spaces, including advanced computer labs equipped for statistical computing, data analysis and optimisation modelling. Core modules integrate software‑enhanced learning, giving students hands‑on experience with tools such as R and Python to explore statistical datasets, build predictive models and solve operational research problems. Throughout the programme, learners engage in collaborative problem‑solving workshops, group tutorials and supervised assignments that sharpen analytical reasoning and communication skills. In their final year, students undertake a substantial independent project, applying theory to complex questions and presenting results both in written form and through interactive data visualisations. Additional opportunities such as optional industry placements and global exchange programmes further enhance professional readiness:

Practical use of statistical and mathematical software, including R and Python, to analyse real datasets and implement computational methods.
Access to specialised computer facilities in the teaching centre for modelling, simulation and optimisation tasks.
Supervised independent project in the final year, with emphasis on applying mathematical and statistical theory to real problems.
Group‑based workshops and tutorials that build teamwork, communication and analytical skills.
Optional year in industry placement with partner organisations to apply classroom learning in financial, technology or analytics settings.
Participation in international work or study experience through IAESTE and Turing exchange programmes.

Programme Overview
This three‑year single honours degree blends core mathematical foundations with statistical methods and operational research techniques. Students develop analytical capabilities for quantitative reasoning, learn how to extract insights from data and gain practical skills for solving optimisation problems. The curriculum prepares learners for careers where data‑driven decisions and analytical rigour are essential, including finance, analytics, consulting and technology sectors.

Practical Skills and Tools
Throughout the degree, students build competencies that are highly sought after in today’s job market:

Quantitative analysis using mathematical modelling and statistical inference.
Data handling and interpretation with modern statistical software and programming environments.
Understanding of optimisation and operational research methods to solve real‑world problems.
Ability to communicate complex quantitative results effectively to diverse audiences.
Teamwork, project planning and professional presentation through group‑based assignments.

Career and Progression Opportunities
Graduates from this programme are well positioned for quantitative and analytical careers in industries such as finance, data science, consulting, risk analysis and technology. The combination of mathematics, statistics and operational research enhances employability and opens pathways to further study in postgraduate degrees, professional qualifications or specialised research.

Why This Matters
By integrating rigorous mathematical learning with practical statistical tools and optimisation techniques, the BSc in Mathematics and Statistics & Operational Research at Queen’s University Belfast equips students with the analytical confidence and technical expertise necessary to tackle complex challenges across sectors — empowering them to succeed in data‑rich, decision‑driven fields.

Progression & Future Opportunities

Graduates of the BSc Mathematics, Statistics and Operational Research programme at Queen’s University Belfast are prepared for careers that combine analytical thinking with practical problem-solving in business, finance, and technology: typical roles include Data Analyst, Operations Research Analyst, Statistician, and Business Analyst. The programme develops a strong foundation in mathematics, statistical modelling, and optimisation techniques, making graduates highly competitive in quantitative and analytical roles.

Progression & Future Opportunities

Support from Queen’s Careers, Employability & Skills, including personalised career guidance, CV and interview preparation, networking events, and access to targeted job opportunities in analytical and quantitative fields.
Strong employment outcomes: around 87 % of graduates in mathematics-related programmes are in employment or further study within 15 months of graduation.
Competitive earning potential: graduates of numerate disciplines typically secure salaries above the national average for new graduates.
Industry experience: opportunities for year-in-industry placements and collaborations with organisations in finance, technology, and consulting, helping to develop practical skills and professional networks.
Degree recognition: awarded by a Russell Group research-led university, providing long-term accreditation value and respect in both academic and professional contexts.

Further Academic Progression
Graduates can pursue postgraduate study such as Master’s or PhD programmes in Statistics, Operational Research, Data Science, Applied Mathematics, or related fields, building on the strong analytical, statistical, and modelling skills acquired during the BSc programme.