Gain an in-depth understanding of economics, econometrics and data science on our new interdisciplinary MSc Economics with Data Science programme.

Combining theoretical training and the teaching of practical tools, you will be taught by experts in both economics and mathematical engineering disciplines and trained on essential software tools in programming and data science, alongside robust economics content, distinctive to this programme.

You will have the opportunity to put your training into practice through industry-led projects, working closely with potential employers to apply your learning to solve real-world problems.

Whether you are looking to pursue a career as a data analyst or quantitative economist, the MSc Economics with Data Science programme will provide you will high quality training and real-world application.

This programme will help you to:

  • Gain advanced skills in both economics and computer science, skills in high demand by employers
  • Evidence hands-on practical experience and build industry connections
  • Be exposed to state-of-the-art software including the Amazon Web Services (AWS) and Python to explore big data in a real-world setting
  • Develop soft skills through working in a professional environment, essential for employment in any sector.

You will have the flexibility to further enhance your skillset by selecting from a variety of optional units to tailor your studies, such as Health Economics, Empirical Industrial Organization, and Program Evaluation.

There are additional opportunities for industry exposure during your dissertation to provide further transferable skills and real-world experience.

All our teaching is research-led and having a direct impact on policy and practice. 94% of the University's research was assessed as either 'world-leading' or 'internationally excellent' (REF, 2021).

Programme structure

In the first term, you will study three compulsory units in economics and data science. In the second term, you can choose two optional units which you will study in addition to a mandatory unit on Machine Learning for Economics. Finally, you will work in a group with fellow students on a project-based dissertation to employ your newly acquired skills.

Visit our programme catalogue for full details of the structure and unit content for our MSc Economics with Data Science.

Entry requirements

An upper second-class undergraduate honours degree or international equivalent in Maths/Engineering/Data Science/Computer Science/Physics.


An upper second-class honours degree or international equivalent in an Economics or quantitative discipline or a related field. This must include a 2:1 in at least 3 quantitative units from the maths qualification requirements list below in the final 2 years of the degree.

See international equivalent qualifications on the International Office website.

Read the programme admissions statement for important information on entry requirements, the application process and supporting documents required.

Go to admissions statement

If English is not your first language, you will need to reach the requirements outlined in our profile level G.

Further information about English language requirements and profile levels.

If your degree subject is not listed in the main entry requirements, you must have evidence of an upper second class honours degree which includes three units of mathematics with 60% or above (or international equivalent) in each unit. Examples of acceptable units include:

  • Advanced Maths (introductory maths does not count towards maths unit requirements)
  • Analysis
  • Auditing
  • Bayesian Modelling
  • Calculus
  • Complex Functions
  • Computer Science (including programming/algorithms)
  • Data Mining/Data Science/Data Analytics
  • Decision Analysis and Simulation
  • Decision Maths
  • Derivatives
  • Differential Equations/Ordinary Differential Equations
  • Discrete Mathematics
  • Econometrics (including 'introductory' 'foundations of'; and 'advanced')
  • Financial Analysis
  • Financial Maths
  • Financial Modelling
  • Financial Reporting
  • Game Theory
  • Geometry
  • Information Theory
  • Investment Analysis
  • Kinematics
  • Linear Algebra
  • Linear Programming
  • Macroeconomics (including intermediate/advanced)
  • Management Science
  • Mathematical Programming
  • Maths for Economics
  • Mechanics (any type of mechanics)
  • Mechatronics
  • Micreoconomics (including intermediate/advanced)
  • Multi Variate Analysis
  • Network Science
  • Number Theory
  • Optimisation
  • Probability
  • Proof/Intro to Proof
  • Pure Maths
  • Quantitative techniques
  • Quantitative Methods
  • Research Methods
  • Statement Analysis
  • Statistics/Statistical Methods/Statistical Analysis
  • Supply Chain management/Logistics Management
  • Time Series Analysis

Fees and funding

UK: full-time
£16,400 per year
Overseas: full-time
£30,500 per year

Fees are subject to an annual review. For programmes that last longer than one year, please budget for up to an 8% increase in fees each year.

More about tuition fees, living costs and financial support.

Alumni discount

University of Bristol students and graduates can benefit from a 25% reduction in tuition fees for postgraduate study. Check your eligibility for an alumni discount.

Funding for 2023/24

Further information on funding for prospective UK and international postgraduate students.

Career prospects

New for 2023. Developing economic data scientists with a strong computational background. Graduates possess a multidisciplinary skillset which can be tailored to a broad range of industries and occupations, such as data analyst or quantitative economist within the financial industry, private sector organisations, or public organisations such as the Government Economic Service.

Graduates are exposed to the Amazon Web Service (AWS) to explore big data in a real-world setting and can evidence industry experience through participation in industry-led projects.

This programme is suited to both professionals and undergraduates seeking advanced training in economics and data science, following a related degree in Economics, Computer Science, Physics, Maths, or Engineering, with exposure to programming/coding.