This is a truly hands-on and forward-looking degree that combines the solid foundations of probability and statistical inference with the practical side of computing and algorithmic thinking. It’s designed for students who want to become confident, data-driven problem-solvers — the kind of graduates who can step into roles in finance, health research, technology, or continue on to advanced postgraduate study.
Year 1
Your first year is all about building a strong base in mathematics, statistics, and computing. You’ll dive into the essentials of probability theory and statistical inference, while also learning to code in at least two programming languages. No previous coding background is needed — you’ll be taught from the ground up, so you can quickly gain confidence in both theory and practice.
Year 2
In your second year, the focus shifts to more advanced material. You’ll study deeper aspects of probability theory, inference, and algorithms, while also tackling an important module in data ethics. The balance of theory and real-world application ensures you’re not just learning concepts in the abstract — you’re seeing how they play out in practice.
Year 3
By your final year, you’ll have the flexibility to shape your path — either by delving into the more mathematical side of the subject or by applying your skills to practical challenges. A key feature is the independent research project, which counts for around a quarter of your workload. Guided by expert staff in the Department of Statistical Science, you’ll carry out your own data-driven investigation, developing both technical expertise and independence.
Focus areas
Core statistical theory
Algorithmic reasoning
Programming in two languages
Data ethics
Supervised independent research project
Flexibility to specialise either mathematically or practically
Learning outcomes
By the time you graduate, you’ll have a strong grounding in probability, inference, and algorithms. You’ll be fluent in multiple programming languages, able to apply statistical methods across fields like finance, health, and technology, and prepared to carry out independent projects from start to finish.
Professional alignment
The programme is accredited by the Royal Statistical Society for students entering between September 2023 and September 2028 — a professional stamp of approval that highlights the quality and recognition of this degree.
Reputation & employability
UCL ranks among the very best in the UK for Statistics and Operational Research, reflecting the department’s academic strength and the value of your degree. Graduates go on to excellent outcomes — from data scientist roles in industry, government, and finance, to highly competitive postgraduate programmes. Employers consistently value the mix of technical, analytical, and problem-solving skills that this programme develops.
At UCL, the BSc Data Science program is all about learning by doing. Instead of just working through theory in textbooks, you’ll be tackling real-world data projects and building the technical skills that today’s industries are looking for. The curriculum puts a big emphasis on practice—whether that’s coding in multiple languages, solving problems in workshops, or taking on applied assignments that make abstract concepts click. All of this happens within the supportive environment of UCL’s Department of Statistical Science, where you’ll find plenty of mentorship and collaborative opportunities to help you grow.
Here’s how experiential learning really comes to life in UCL’s Data Science BSc:
Projects that matter – From small individual and group assignments to a major final-year research project under the guidance of expert UCL faculty, you’ll get to apply what you’ve learned in meaningful ways.
State-of-the-art facilities – Access modern computing labs and spaces across UCL’s central London campus, perfect for coding, running simulations, and testing models in practice.
Programming from the start – You’ll train in widely used languages like Python and R right from year one, moving on to more advanced applications as you progress.
Learning in small groups – Tutorials and computer workshops give you the chance to dive deep into areas like machine learning and statistical inference, while getting direct feedback from your lecturers.
Cross-disciplinary experience – Explore modules and initiatives that connect data science with fields like medicine, finance, and natural sciences, exposing you to real-world applications of data across sectors.
Unlimited academic resources – Take advantage of UCL’s world-class libraries, such as the Science Library, with access to a vast range of journals, digital resources, and specialist material.
Networking and inspiration – Attend departmental events, guest lectures, and seminars with top data scientists and UCL alumni, where you’ll hear first-hand about career journeys and industry challenges.
With this combination of hands-on learning, expert support, and real-world exposure, you’ll graduate with the confidence and skills to make an impact wherever data is shaping the future.
Graduates of UCL’s BSc Data Science program have excellent career prospects. Many move directly into roles such as Data Scientist, Business or Data Analyst, Finance Analyst, or Technology Consultant, showing just how versatile the skills gained on the course really are. The degree blends practical training with a solid theoretical foundation, giving students everything they need to thrive in today’s data-driven world.
Dedicated support is available through UCL Careers. Students benefit from one-to-one career advice, CV and application workshops, employer networking events, and help in securing internships. This support is especially strong in the tech, finance, and analytics sectors, where demand for data skills is growing rapidly.
Graduate outcomes are consistently positive. Around 85% of recent graduates in Statistics and Data Science are either working or pursuing further study within 15 months. Typical starting salaries range from £35,000 to £52,500, depending on sector and role, placing graduates in a competitive position right from the start.
Strong industry connections make a real difference. Partnerships with leading firms such as Accenture, Google, Deloitte, IBM, and Morgan Stanley help students access internships and graduate roles, creating a clear pathway from university to employment.
Professional recognition adds extra value. The program is accredited by the Royal Statistical Society, giving graduates an additional layer of professional credibility that supports long-term career growth.
Most importantly, graduates feel their studies matter. Surveys show that 70–75% of alumni find their work meaningful and closely linked to their degree, with many going on to highly skilled roles in IT, finance, research, and beyond.
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