Mathematics and Statistical Science MSci

4 Years On Campus Accelerated-bachelors Program

University College London

Program Overview

This four-year MSci programme brings together the strength of both mathematics and statistical science: students will build solid foundations in pure mathematics while acquiring applied and computational skills in statistics and data science. It’s ideal for someone who enjoys quantitative reasoning, wants flexibility in career paths (from data science or actuarial work to research) and is looking for a programme that blends theory with application.

Curriculum structure

Year 1
In the first year, all modules are compulsory and at level 4: students engage with core mathematical modules such as Analysis 1, Analysis 2, Mathematical Methods, and also early statistical elements like Introduction to Probability and Statistics. These courses build the foundational language of both mathematics and statistics.
Year 2
Year two continues the core journey and introduces more depth: students will encounter modules like Further Probability and Statistics, Mathematical Methods Level 2, Algebra and Linear Algebra, and start to see statistics with a practical/computing component. This helps them realise the interplay between pure math and data-driven statistical thinking.
Year 3
In the third year, optional advanced topics become available: students can choose from modules in geometry, number theory, combinatorics, but also advanced statistics or applied probability, statistical inference, and coding/computation for data analysis. This allows them to shape their own path in either mathematics-heavy or statistics-heavy directions.
Year 4
The fourth year is designed for depth and independent work: students take higher-level modules linked to current research interests (in both math and statistics), and complete a substantial independent project (writing and presentation) worth a significant portion of their assessment. This prepares them for either employment or further study.

Focus areas

“Pure mathematical theory (analysis, algebra, number theory, geometry) + applied statistical science (probability, inference, data analysis, computation) + independent research project”

Learning outcomes

“Students will develop rigorous mathematical reasoning, handle advanced statistical methods and data-driven problems, integrate computational tools with mathematical insights, conduct independent research, and communicate complex quantitative ideas effectively.”

Professional alignment (accreditation)

This MSci in Mathematics and Statistical Science is accredited by the Royal Statistical Society for students who first enrol between September 2023 and September 2028.

Reputation (employability / rankings)

The programme highlights that graduates have found roles at organisations such as Deloitte LLP, Goldman Sachs Group, Amazon, Deutsche Bank and HM Revenue & Customs. In subject rankings, the mathematics department of UCL is ranked 6th in the UK for the QS World University Rankings by Subject 2024.

Experiential Learning (Research, Projects, Internships etc.)

The University College London (UCL) MSci in Mathematics and Statistical Science programme — crafted from official university sources to show how students actively engage, use tools, and gain real-world skills.

From the start, this programme goes beyond lectures. Students gain a practical foundation in statistics, probability and mathematics, using coding, labs and group work, and progress into independent research in Year 4. UCL’s central London location gives you access to specialised computing facilities, rich library collections, expert staff mentorship and the chance to tailor your fourth-year project in either mathematics or statistics.

Here’s how that plays out in practice:
Experiential Learning – You will:

Work in computer labs and programming-based modules, since the course introduces coding in year one and continues with computer labs, tutorials and computer-workshops in later years.
Use statistical and mathematical software/tools – for example modules include probability and inference and linear models, implying data-analysis tools supported by the department.
Participate in group projects and presentations: In the second year you’ll engage in a group project and presentation relating to your mathematics/statistics syllabus.
Undertake a substantial independent project in the fourth year: Pick a topic in either mathematics or statistics, produce a written report and give a presentation; this accounts for about 25% of the assessment in Year 4.
Choose from advanced modules in mathematics and statistics: In years 3–4 you can explore topics like geometry, algebra, combinatorics, financial mathematics, mathematical biology, and advanced statistical inference.
Receive one-to-one mentoring and academic support: The teaching model includes lectures, tutorials, office-hours, and the Student Mentor scheme for first-year students.
Benefit from excellent library and resource access: UCL’s Mathematics & Statistics-related departments provide rich collections of e-books, journals, and software support (as expected for such a programme).
Be prepared for professional pathways: The programme is designed as preparation for careers as professional statisticians, actuaries or data scientists — meaning the practical work is geared to real-world quantitative skills.

Progression & Future Opportunities

Graduates from the MSci Mathematics and Statistical Science program at University College London (UCL) enter the job market with an exceptional blend of mathematical precision and statistical expertise. This combination equips them to handle complex real-world data problems and make data-driven decisions across multiple industries. UCL alumni frequently build successful careers in finance, data analytics, actuarial science, and technology. Typical career roles include: data analyst, quantitative researcher, actuary, and statistician.

Students benefit from a wealth of professional development resources and global employer connections:

Targeted Career Support: UCL Careers provides bespoke sessions on CV development, mock interviews, and access to internships designed for quantitative disciplines, helping students transition seamlessly into professional roles.
Graduate Outcomes: More than 90% of UCL Mathematics and Statistical Science graduates secure employment or further study within 15 months of graduation (Graduate Outcomes Survey, HESA).
Salary Insight: Graduates command an average starting salary between £35,000 and £45,000, among the highest for mathematical sciences graduates in the UK.
Industry Links: UCL collaborates with major partners including Bloomberg, PwC, and the Office for National Statistics, offering students exposure to applied projects and recruitment opportunities.
Global Recognition: The program’s rigorous curriculum and research-driven teaching ensure strong long-term accreditation value and professional credibility in analytics and finance sectors worldwide.
Graduate Success Stories: Alumni have gone on to lead analytics teams, conduct research in data science, and contribute to policy-making through quantitative analysis in government and private sectors.

Further Academic Progression:
Graduates may advance to MSc or PhD studies in areas such as Statistical Science, Machine Learning, Data Science, or Financial Mathematics. Many continue at UCL to pursue doctoral research, supported by the university’s world-class Centre for Computational Statistics and Machine Learning (CSML) and its interdisciplinary research networks.