Computational Finance with a Year in Industry MSc

2 Years On Campus Masters Program

Royal Holloway University of London

Program Overview

The MSc in Computational Finance with a Year in Industry is an exciting two-year master’s that blends advanced quantitative finance with real-world industry experience. It is designed for students who want to become experts in financial modelling, risk analysis, and computational methods for complex markets. You’ll explore cutting-edge techniques in machine learning, statistical finance, and data-driven decision-making while gaining practical exposure through a full-year placement with leading financial and tech organisations.

Curriculum Structure

Year 1
In your first year, you will build a strong foundation in both finance and advanced computing. Core modules such as Data Analysis, Foundations of Finance, and Investment & Portfolio Management equip you with essential quantitative skills, from exploring machine learning and Bayesian methods to understanding modern theories of asset pricing and strategic portfolio construction. Alongside modules like Ethics in Advanced Computing and Artificial Intelligence, you will undertake an Individual Project, giving you the chance to integrate what you’ve learned through independent work.

Year 2 – Year in Industry + Final Project
The second year is highly practical and career-focused. You will embark on a Year in Industry placement where you apply your skills in a real workplace setting, supported by the Department and Careers Service. This not only enhances your learning but also significantly boosts employability. After your placement, you will complete an extended Individual Project under academic supervision, where you can delve into research or implementation work that builds directly on your industry experience.

Focus Areas

Modern quantitative finance, computational modelling, machine learning applications in finance, risk assessment, programming for data analysis, and real industry experience.

Learning Outcomes

Graduates will be able to critically evaluate and apply computational finance techniques to practical problems, implement machine learning and quantitative methods using tools like MATLAB and R, and solve data-intensive challenges in financial environments with confidence.

Professional Alignment (Accreditation)

This programme draws on rigorous academic standards from both the Department of Computer Science and the Department of Economics and includes an industry placement that enhances professional readiness and supports strong employer links.

Reputation (Employability & Rankings)

Royal Holloway is ranked among respected institutions globally, offering excellent career support and industry engagement to help students stand out after graduation.

Experiential Learning (Research, Projects, Internships etc.)

At Royal Holloway, this programme is designed so you don’t just learn theory — you apply your skills in real-world contexts and industry settings. From the start, you’ll work with industry-standard quantitative and analytical tools such as MATLAB and R, and gain experience managing and querying data with SQL and relational databases. You’ll also have access to state-of-the-art computing facilities, including a high-performance computing cluster with GPU capabilities, which supports large-scale data analysis and advanced algorithm work. In addition, a weekly seminar series brings professionals to campus so you can hear directly from experts and begin building valuable industry connections:

This immersive learning experience includes:

Industry placement year: In your second year, you spend a full year on a work placement where theory meets practice, tackling real business challenges with guidance from the Department and Careers Service.
Hands-on training with real tools: Extensive use of MATLAB, R, database systems, and object-oriented programming helps you develop practical software and analytics skills that employers actively seek.
High-performance computing infrastructure: You can access a dedicated computing cluster with large storage, GPU servers, and data processing tools for complex modelling and data-intensive projects.
Professional seminars and workshops: Weekly talks and workshops run by industry professionals bridge academic knowledge and workplace readiness.
Collaborative group work and project assessment: Many modules include small group projects or coursework that develop teamwork, communication, and problem-solving in realistic scenarios.
Career support services: Tailored employability support includes one-to-one coaching, interview preparation, and careers events with employers to help you secure placements and future roles.

Progression & Future Opportunities

Graduates from this programme move into exciting careers where advanced quantitative skills meet real-world financial and data challenges. You’ll be well-prepared for roles such as Quantitative Analyst, Data Scientist, Risk Analyst, or Financial Software Developer, with many students securing employment even before completing their placement year thanks to the strong industry connections and practical experience gained during the course.

Here’s how this degree helps you build your career:

University career support: The Royal Holloway Careers and Employability Service offers one-to-one coaching, CV and interview workshops, and employer events specifically tailored to this programme. The department also provides guidance to help you find and succeed in your placement and graduate roles.
Employment outlook: Students who complete a year in industry enjoy high employability, with many entering skilled roles across technology and finance sectors shortly after graduation.
Industry connections and partnerships: Placement students have worked with leading companies such as UBS, Shell, Rolls Royce, Société Générale, and VMware, providing networking opportunities and potential pathways to graduate employment.
Long-term accreditation value: The programme combines the strengths of the Department of Computer Science and the Department of Economics, blending rigorous technical training with practical applications — a combination highly valued by employers in finance, technology, and data roles.
Graduate outcomes: Many students secure positions directly related to their placement experience, and the combination of real industry work with advanced academic learning enhances confidence and readiness for professional challenges.

Further Academic Progression:
After completing this master’s, you could continue to a PhD in Computational Finance, Machine Learning, or Data Science, supported by Royal Holloway’s active research community. Alternatively, professional qualifications such as Chartered Financial Analyst (CFA) or Professional Risk Manager (PRM) can complement the technical skills you’ve developed and strengthen your profile for advanced finance and analytics roles.