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MSc Financial Mathematics with Data Science

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Course Description

Develop a strong foundation of quantitative, mathematical and computational skills relevant to a career in the financial sector.

Finance is a dynamic industry, with innovation in quantitative methods driving fast-growing areas such as FinTech. Advances in machine learning and increased availability of data are allowing organisations to make better decisions and improve their products and services.

Implementing these advances requires a new generation of graduates with a range of skills in quantitative, mathematical and data science fields. Skills in data science are increasingly sought after by industry.

This course will reinforce your mathematical skills across a wide range of topics and equip you with quantitative skills desired by employers in the financial industry. You’ll gain a broad education in mathematical and data science methods relevant to modern financial institutions. You’ll develop a practical and theoretical understanding of machine learning and other data science tools, and the software skills to successfully implement them.

Entry Requirements

You should have a first or strong second-class undergraduate degree or international equivalent.

To apply for this course, your undergraduate degree should be in a programme that incorporates a substantial mathematical element such as mathematics, statistics, computer science, physics, chemistry, engineering or economics. Computer programming experience would also be advantageous.

We will also consider other subjects, for example geography or biology, which may meet the criteria depending on their specific mathematical and computing content.

We may make an offer based on a lower grade if you can provide evidence of your suitability for the degree.

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Fees

For fees and funding options, please visit website to find out more

Student Destinations

On graduation, you’ll have a broad range of skills and knowledge relevant to a career in traditional and modern financial sectors. From banking, insurance, investment and risk management, to leading areas of the modern financial industry such as FinTech, employers are seeking specialists with financial mathematics and data science skills. Our dedicated careers team offers individual guidance and can help you decide between employment and further study.

Recent graduates from the department are in positions in a wide range of financial sectors including: foreign exchange trading, credit risk, fund management, insurance and actuarial consulting in companies ranging from start-up FinTech companies to multi-national, big-name banks and insurers.

Module Details

Compulsory course units

These compulsory units are currently being studied by our students, or are proposed new units.

Semester 1

  • Programming for data science
  • Discrete time finance
  • Applied machine learning
  • Risk, randomness and optimisation

Semester 2

  • Mathematics of machine learning
  • Continuous time finance
  • Advanced mathematics and data science techniques for finance
  • Monte Carlo methods for finance
  • Research project preparation

Summer

  • Individual research project

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