Course information

Department

Computing
Institute of Management Studies

Length

1 year full-time, 2-3 years part-time

Course overview

The MSc Data Science and Financial Technology pathway will provide you with the technical and practical skills on how to use the technologies in investment analysis, algorithmic trading, risk management, and payment and fraud detection.

The rate at which society is creating data is rapidly accelerating; outstripping our ability to successfully analyse and use it. The MSc in Data Science and Financial Technology will give you the skills to join the next generation of data scientists, leading the way in areas from climate change to financial forecasting.

Why study MSc Data Science and Financial Technology

  • You’ll learn the fundamentals of data science, gaining foundational skills in statistics, data mining, data visualisation, programming and machine learning, giving you the skills and techniques to efficiently analyse very large data sets.
  • You’ll combine this with specialist modules in financial technology such as blockchain, to redesign many of the existing processes in banking and finance.
  • This degree is interdisciplinary, and you’ll learn from experts in the Department of Computing and the Institute of Management Studies. Many faculty members bring their knowledge from active research and consultancy in the areas of FinTech, data science, computing and financial technologies.
  • You’ll carry out original analysis on real-world financial data through your final project, which allows you to focus on your specific research interests.
  • With guidance from experts, you’ll learn to use industry-standard software such as Apache, Hadoop and R to analyse data from industries such as biomedical, financial and social media.
  • Our close links with industry mean that you’ll have the opportunity to learn from industry experts in guest lectures throughout the year. 

Pathways

As well as MSc Data Science and Financial Technology, we have the following pathway options that give you the chance to specialise in a particular industry area. For each MSc Data Science pathway, in addition to the pathway-specific skills, you’ll learn core skills that are essential for data scientists such as statistical analysis, programming, machine learning, data visualisation, and big data technologies.

In collaboration with Goldsmiths Institute of Management Studies, you’ll learn the skills to become the next generation of data science experts in sectors ranging from healthcare to business.

The pathway options are:

Contact the department

If you have specific questions about the degree, contact V L Raju Chinthalapati or Alan Zucconi.

What you'll study

Compulsory modules

You'll take the following compulsory modules:

Module title Credits
Data Programming 15 credits
Statistics and Statistical Data Mining 15 credits
Financial Data Modelling 15 credits
Blockchain Programming 15 credits
Mathematics for Financial Markets 15 credits
Big Data Applications 15 credits
Final Project in Data Science 60 credits

Optional modules

You'll also take two optional modules from across the Department of Computing and Institute of Management Studies to the value of 30 credits. These vary from year to year, and may include the following:

Module title Credits
Econometrics 15 credits
From National Statistics to Big Data 15 credits
Advanced Econometrics 15 credits
Marketing Strategy 15 credits
Marketing Analytics 15 credits
Digital Marketing and Branding 15 Credits
Data Visualisation 15 Credits
Artificial Intelligence 15 credits
Neural Networks 15 credits
Machine Learning 15 credits
Data Science Research Topics 15 credits
R Programming 15 credits

Download the programme specification.

Please note that due to staff research commitments not all of these modules may be available every year.

Entry requirements

You’ll gain a strong foundation in data science and specialist knowledge in a particular field. We do not assume that you will have programmed before, but we do require a level of mathematical dexterity that is commensurate with having completed a numerate degree.

You’ll require a BA or BSc Degree at 2.1 level or above in subjects like computer science, mathematics, statistics, engineering, economics or finance.

International qualifications

We accept a wide range of international qualifications. Find out more about the qualifications we accept from around the world.

If English isn’t your first language, you will need an IELTS score (or equivalent English language qualification) of 6.5 overall and no element lower than 6.0 to study this programme. If you need assistance with your English language, we offer a range of courses that can help prepare you for postgraduate-level study.

Fees, funding & scholarships

Annual tuition fees

These are the fees for students starting their programme in the 2024/2025 academic year.

  • Home - full-time: £12520
  • Home - part-time: £6260
  • International - full-time: £20460

If your fees are not listed here, please check our postgraduate fees guidance or contact the Fees Office, who can also advise you about how to pay your fees.

It’s not currently possible for international students to study part-time under a student visa. If you think you might be eligible to study part-time while being on another visa type, please contact our Admissions Team for more information.

If you are looking to pay your fees please see our guide to making a payment.

Additional costs

In addition to your tuition fees, you'll be responsible for any additional costs associated with your course, such as buying stationery and paying for photocopying. You can find out more about what you need to budget for on our study costs page.

There may also be specific additional costs associated with your programme. This can include things like paying for field trips or specialist materials for your assignments. Please check the programme specification for more information.

Funding opportunities

Find out more about postgraduate fees and explore funding opportunities. If you're applying for funding, you may be subject to an application deadline.

How to apply

You apply directly to Goldsmiths using our online application system. 

Before submitting your application you’ll need to have:

  • Details of your academic qualifications
  • The email address of your referee who we can request a reference from, or alternatively a copy of your academic reference
  • Copies of your educational transcripts or certificates
  • personal statement – this can either be uploaded as a Word Document or PDF, or completed online. Please see our guidance on writing a postgraduate statement

You'll be able to save your progress at any point and return to your application by logging in using your username/email and password.

Find out more about applying.

Careers

Prepare yourself for a career in data science

We carefully designed our data science programme to help you to become successful data science and FinTech professionals. Core modules of the individual pathways provide you with a solid grounding in the theory of big data, statistics, machine learning and the pathway domain. Further, we train you on the latest technologies like blockchain programming and methods and techniques in quantitative finance so that you can be an important resource for different organizations as blockchain programmer, FinTech specialist, financial analyst as well as a data scientist and engineer. The programme provides you with the opportunity to learn the core techniques and further it enhances your learning through lab sessions. The lab sessions are going to help you to build hands-on experience on data science and FinTech tools prior to your graduation.

The learning outcomes of all modules are in line with the fundamentals and current trends of data science and token economy what exactly employers need and want. Each module provides you with hands-on experience of real-world applications, analysing data sets such as social media and financial data while working with industry standard software tools. Our Industry Advisory Board (IAB) that has experts from industry who can guide us from time to time on the industry requirements. Most of the data science programme faculty have worked with industry over many years. The teaching for the data science pathways is always in line with the current trends and technologies of data science. Moreover, while doing your masters, you will have cutting edge computing facilities for big data analysis and opportunity to work with the leading researchers towards your final projects.

With successful completion, our data science students can take up wide variety of roles across many organisations.

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