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3 Years On Campus Bachelors Program
Royal Holloway University of LondonThe BSc (Econ) in Economics and Data Science at Royal Holloway combines traditional economics training with modern data science skills. You’ll gain the ability to think like an economist while becoming fluent in programming and data analysis. It’s perfect for anyone who enjoys maths, coding, and exploring how data can explain real-world economic trends.
Curriculum Structure
Year 1
In your first year, you’ll build a strong foundation in economics and quantitative methods. Core modules include Principles of Economics, Mathematics for Economics, Applied Economics and Policy, Data Skills for Economists, and an Employability module to get you ready for the next stages of your studies.
You’ll start learning programming and data manipulation, often using Python or R, through Data Skills for Economists. Alongside this, micro- and macroeconomic theory will help you develop a solid economic intuition.
Year 2
The second year dives deeper into both economics and data science. Modules include Econometrics 1 & 2, Game Theory and Behaviour, Financial Markets & Institutions, Industrial Growth and Competition, and potentially your first Introduction to Data Science or Economic Modelling and Data Science modules.
Here, you’ll learn how to apply statistical methods, model strategic interactions, and link economic questions with data analysis, using Python or R.
Year 3
In your final year, you’ll focus on specialisation and honing your skills. You’ll complete core data science modules (at least 30 credits) and choose electives in economics or data science. Options may include Time Series for Macroeconomics with Data Science, or modules in web scraping, machine learning, data visualisation, or applied economic research.
You’ll also take a final-year Employability module to support your transition into the workplace or further study.
Focus Areas
Economics
Statistical Inference
Programming & Data Analytics
Machine Learning
Empirical Economic Research
Learning Outcomes
Graduates will be able to:
Model economic problems using quantitative methods
Program in Python or R
Analyse large datasets and draw meaningful conclusions
Visualise and communicate data-driven insights in an economic context
Professional Alignment (Accreditation)
This program follows the UK’s QAA Framework for Higher Education Qualifications, ensuring it meets national standards. Students may also gain some exemptions from the Chartered Institute of Management Accountants (CIMA) after completing the course.
Reputation (Employability / Ranking)
Royal Holloway is ranked 35th in the UK in the Complete University Guide (2026) and around #461 in the QS World University Rankings. The university has a student satisfaction rate of 82.9% (2025). Economics graduates are highly sought after, with a social mobility rate of 4.1%—well above average—and Royal Holloway reports over 90% of students are employed or in further study soon after graduation.
At Royal Holloway, students on the Economics and Data Science program gain substantial hands-on experience that bridges theory and practice. From day one, you'll be actively applying economic models to real-world data, using programming and analytical tools to extract insights. The course emphasizes practical learning through projects, research, and industry-standard software, ensuring you develop skills that are immediately relevant in the job market. Modern facilities, expert guidance, and collaborative opportunities make the learning environment highly interactive and career-focused.
Students benefit from a range of experiential opportunities, including:
Practical Projects: Work on real-world case studies, programming assignments, and data visualisation projects.
Industry-Relevant Software: Gain proficiency in Python and R, with pathways to professional certifications.
Data Lab Facilities: Access to newly created data labs equipped for advanced data analysis and machine learning.
Research Opportunities: Collaborate with leading researchers on innovative economic and data science projects.
Placement Year: Option to undertake a Year in Business, gaining industry experience and networking opportunities.
Group Work and Collaboration: Participate in team-based projects to solve complex economic and data problems.
Portfolio Development: Build a strong portfolio showcasing practical skills in programming, data analysis, and economic modelling.
This combination of resources, hands-on learning, and industry connections ensures students leave prepared to make an immediate impact in data-driven economic roles.
Graduates of the BSc (Econ) Economics and Data Science program at Royal Holloway University of London enjoy strong employability, entering diverse sectors such as finance, technology, and government. Typical roles include Data Analyst, Financial Consultant, and Economic Forecaster, offering both intellectual challenge and competitive starting salaries:
University Careers Services: Dedicated career support, CV workshops, mock interviews, and access to industry networking events.
Employment Stats & Salary Figures: Graduates often secure positions within six months of graduation, with starting salaries in the range of £25,000–£35,000, depending on sector and role.
University–Industry Partnerships: Collaborations with leading financial institutions, tech companies, and research organisations enhance practical learning and employability.
Long-term Accreditation Value: The degree is widely recognised by employers and professional bodies, providing a strong foundation for career progression.
Graduation Outcomes: Alumni move into roles in data science, economic consultancy, analytics, and policy-making, leveraging hands-on experience in programming, data visualisation, and machine learning.
Further Academic Progression:
Students may continue their studies with postgraduate programs in Economics, Data Science, Financial Analytics, or Business Analytics, or pursue professional qualifications in finance, data analytics, and related fields to deepen expertise and expand career opportunities.
A Levels: AAB-ABB / A-level MathematicsAt least five GCSEs at grade A*-C or 9-4 including English and Mathematics.IB: 6,6,5 at Higher Level including Maths with a minimum of 32 points overall.For Indian Applicants: Achieve a grade of 80% overall in your Higher Secondary School Certificate with 80% in any A-level subject specified aboveFor US Applicants: Applicants must either achieve a 4 in at least two relevant AP exams, a composite ACT score of 25 (including writing) with a 4 in an AP or B in a specified A-Level subject, or an SAT score of 1100 with a 4 in an AP or B in a specified A-Level subject.AP Calculus BC or an equivalent college course is required for Computer Science and Electronic Engineering.IELTS: 6.5 overall. Writing 7.0. No other subscore lower than 5.5.TOEFL iBT: 88 overall, with Reading 18 Listening 17 Speaking 20 Writing 26.Data AnalystStatisticianData ScientistBusiness AnalystQuantitative AnalystActuaryOperations Research AnalystFinancial AnalystMarket Research AnalystRisk AnalystData EngineerMachine Learning EngineerBiostatisticianEconometricianArtificial Intelligence Specialist
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