University course Β· real outcomes from HESA / Discover Uni Β· part of Careermash
University degree

Statistical Science

University College London Β· London
Qualification
Degree
Length
4 yrs
UK fees / yr
Β£9,535
Study
full-time
Robin Β· your guide
Here's the honest picture on this course - what you'd study, whether you'd likely get in, what it pays, and where it leads. Everything's real data.
About this course

Statistical science is the discipline concerned with the collection, analysis, and interpretation of data in the presence of uncertainty. It provides the mathematical and methodological foundation for drawing reliable conclusions from evidence, quantifying what we know, and communicating confidence honestly. Statistics underpins research across the natural and social sciences, medicine, economics, finance, and engineering, and the ability to work with data rigorously is increasingly central to a wide range of professional roles as the world becomes more data-rich and decision-making becomes more quantitative.

At University College London, this four-year full-time Statistical Science (International Programme) degree combines rigorous training in statistical theory and methods with study at a partner institution abroad, providing experience of a different educational and cultural environment. You will develop expertise in probability, statistical inference, regression, multivariate analysis, computational statistics, and the foundations of modern data science and machine learning. The international component broadens your horizon and prepares you for careers with a particular emphasis on international expertise, whether in multinational organisations, international research collaborations, or roles that require engagement across different cultural and regulatory environments.

UCL's statistical science department is research-active and connected to the wider research communities of London's universities and medical centres, providing a rich context for learning.

You will graduate with strong quantitative skills, the capacity to work with complex data across a range of modelling frameworks, and the international experience that distinguishes this programme from conventional statistics degrees.

Graduates from statistical science programmes work in actuarial science, financial modelling, biostatistics and clinical trials, government statistical services, data science, machine learning, research, and consultancy. The quantitative rigour of a statistics degree is valued across virtually every industry that uses data to make decisions. Postgraduate study in statistics, data science, or a quantitative discipline is a natural continuation for those who want to develop deeper expertise or pursue research careers.

Could you get in?
The grades students arrived with
<48 pts3%
48-63 pts10%
64-79 pts1%
80-95 pts3%
96-111 pts2%
112-127 pts2%
128-143 pts4%
144-159 pts10%
160-175 pts12%
176-191 pts6%
192-207 pts12%
208-223 pts12%
224-239 pts7%
240+ pts9%
How they qualified
81% got in with A-levels. The rest came in a mix of ways:
A-levels81%
another degree7%
the IB6%
other higher education4%
no formal qualifications1%
Could I get in? Try your grades
120 UCAS pts
Pay & prospects
90%
In work or further study after
93%
Continue past first year
86%
Student satisfaction
What graduates earn over time
Β£41,500
After 15 months
Β£41,500
3 years on
Β£57,000
5 years on
What graduates actually go on to do % of leavers
Business, Research and Administrative ProfessionalsHighly skilled25%
Information Technology ProfessionalsHighly skilled20%
Finance ProfessionalsHighly skilled20%
Managers, directors and senior officialsHighly skilled10%
Business and public service associate professionalsHighly skilled10%
Teaching ProfessionalsHighly skilled5%
What students say National Student Survey
86%
of students are satisfied with the course overall
Teaching86%
Assessment & feedback80%
Academic support73%
Well organised84%
Learning resources91%
Student community91%
In students' own words
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Highly recommend
I was sceptical before starting β€” now I'd recommend it to anyone. The best part: the cohort are bright and motivated, which makes the learning environment great. If I'm honest, first-year classes can be quite large. On the city β€” good trans…
Class of 2023 Β· Full-time
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Highly recommend
I've grown so much academically and personally here. The best part: the opportunity to do independent research in the final year is a highlight. If I'm honest, would like to see more industry guest speakers in later years. On the city β€” loc…
Final year Β· Full-time
More courses like this
Where this degree can lead
Like the look of it?
When you're ready, the full entry requirements and application are on University College London's own site.
Apply on uni site
Careermash Β· real course data from HESA / Discover Uni, in plain English.

Career data: role, pay and progression profiles built for Careermash's careers engine; AI-impact estimates from Anthropic's observed AI-usage telemetry and OpenAI's AI Jobs Transition Framework. Course data: HESA / Discover Uni, including Graduate Outcomes, LEO and the National Student Survey. Apprenticeships: IfATE-published standards, approved only.

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