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Edoardo Di Molfetta studied on the MSc Business Analytics at Cass Business School. In this video, Edoardo tells us about his competitive practise of MMA fighting has taught him resilience and confidence and made him fiercely competitive, skills he used on the course.


Who is it for?

The MSc in Business Analytics programme will help you generate and capture greater competitiveness in data-driven business.

Our Business Analytics programme is designed to provide a foundation to those who will determine the scope and direction of data analytics research within their organisation, and communicate the research outcomes to the ultimate decision-makers.

Our graduates are trained to participate in the strategic management process, improve the organisation’s financial performance and help design the effective measures of performance of an organisation for which evidence-based data become a strategic asset in the decision-making process.

Therefore, the primary goal is to provide an insight into business data analytics and prepare the students to develop the set of skills and attitudes that will evolve into effective leadership skills.

Typical backgrounds of students are Accounting, Biology, Business Administration/Studies, Computer Science, Economics, Engineering, Environmental Studies, Finance, Hospitality Management, Human Resources, Information Systems/Technology, Management, Marketing, Mathematics and Psychology.


The main purpose of the master's in Business Analytics programme is to develop a comprehensive set of skills and to encourage the positive attributes that are essential to becoming a successful business analyst.

The master's degree is committed not only to imparting specialist skills, but also to developing the so-called "soft skills” which are important in influencing people and organisations.

As well as obtaining effective and persuasive communication skills, you will also learn about ethics-related issues, which are another key ingredient to responsible leadership.

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On the master's in Business Analytics, you will learn to:

  • Extract valuable information from the data in order to create a competitive advantage
  • Make use of analytical skills to evaluate and solve complex problems within the organisation’s strategic perspective
  • Present and explain data via effective and persuasive communication
  • Show commercial focus and the ability of strategic thinking
  • Demonstrate depth and breadth of using analytical skills to interrogate data sets
  • Illustrate professional integrity and show sensitivity towards ethical considerations.

Induction Weeks

All of our MSc courses start with two compulsory induction weeks which include relevant refresher courses, an introduction to the careers services and the annual careers fair.

Assessment methods


To satisfy the requirements of the degree course, students must complete:

  • Eight core modules (15 credits each)
  • Four elective modules (10 credits each)
  • One applied research project (20 credits).

Assessment of modules on the MSc in Business Analytics, in most cases, is by means of coursework and unseen examination. Coursework takes a variety of formats and may consist of individual or group presentations/reports, set exercises or unseen tests.

Professional development

There is a compulsory one week induction programme just before Term 1 starts, which is a dedicated introduction to the course and to business analytics. You are required to complete a number of induction workshops at the beginning of the course as follows:

  • Team building
  • Career induction and careers fair
  • Professional development skills.

During this period, a variety of activities are offered to students, to support them in their learning and professional development. Cass Careers offers workshops with a focus on the key skills that employers are looking for, as well as preparing students for the application process. The annual MSc Careers Fair at this time provides the opportunity to meet more than 60 companies who are recruiting across many sectors including consulting, insurance, finance, energy, and other fields.

During the year you will also get the opportunity to attend employer events such as recruitment sessions designed to make you more aware of the job opportunities and career pathways open to you. There will also be industry information sessions to help you build and maintain your commercial awareness, a key skill which employers are looking for in their candidates. Examples of the employers who are set to meet the Business Analytics students this year are Accenture, British Airways, Ekimetrics and EY.

Cass Careers also provides a range of workshops and online resources and one-to-one appointments to help you gain key employability skills and information to help you with your career planning and throughout the job search process.

Ask a student

Chat to one of our current master's students now about applying for a MSc at Cass.

Term dates

Term dates 2020/21

In-Person ID Checks (all students must attend): Commences 14 September 2020

Compulsory Induction: 14 - 25 September 2020

Term I
28 September 2020 - 11 December 2020
Term I exams
04 January 2021 - 15 January 2021

Term II
18 January 2021 - 02 April 2021
Term II exams
19 April 2021 - 30 April 2021

Term III
03 May 2021 - 02 July 2021
Term III exams
05 July 2021 - 16 July 2021

Resit period
Students who are required to resit an examination or invigilated test will do so in the period:
09 - 27 August 2021

Submission deadline for Business Research Project or Applied Research Project 
1 September 2021

Official Course End Date
30 September 2021


Course timetables are normally available from July and can be accessed from our timetabling pages. These pages also provide timetables for the current academic year, though this information should be viewed as indicative and details may vary from year to year.

View academic timetables

Please note that all academic timetables are subject to change.

Teaching staff

Course Director - Dr Vali Asimit

Vali's research interests include analysis of multidimensional extremes, robust decision making and robust data visualisation.

Module Leaders of the compulsory Business Analytics core modules

Dr Daniel Beunza

Daniel is Associate Professor in Management and he is the Module Leader in Leadership and Organisational Behaviour. Daniel is an award-winning instructor with years of experience in teaching MBA students at Columbia Business School, MSc students at the London School of Economics and bank executives in the City of London. Daniel’s research examines the role of technology in organisations, and his study of the use of algorithms in the New York Stock Exchange was recently profiled in the Wall Street Journal.

Alan Chalk

Alan is a Data Scientist at Sabre Insurance Company Limited where he applies Machine Learning techniques to insurance related tasks.  He started his career as an Actuary and worked in in non-life insurance where his focus was on predictive analytics and pricing.  Whilst serving as Global Aerospace Actuary at American International Group (AIG) UK, Alan worked with AIGs dedicated Machine Learning Team.  Following this, he expanded his training in statistics and data science with an MSc in Statistics at Sheffield University and an MSc in Machine Learning at University College London.  Alan teaches the Term 3 Applied Machine Learning Module.  He is also part of the MSc in Business Analytics Industry Partners Programme that offers industry-based projects designed by Alan that aim to enhance the experiential learning when the Term 3 Applied Research Project is developed.  Such projects are directly supervised by the industry partner contact person(s).

Dr Oben Ceryan

Oben is a Lecturer in Operations and Supply Chain Management and he is the Module Leader of the Revenue Management and Pricing module.  He obtained his PhD degree in engineering from the University of Michigan.  His research interests are in dynamic pricing and revenue management, an emerging area that aims to enhance firms’ profitability by aligning demand with constrained supply through the integration of operations and marketing decisions and that is applicable to a wide range of industries from manufacturing to hospitality, and from online marketplaces to retailing.

Dr Rosalba Radice

Rosalba is a Reader in Statistics and she is the Module Leader of the Quantitative Methods and the Analytics Methods for Business modules. She obtained her PhD degree in Statistics from the University of Bath. Her research interests are in distributional regression, simultaneous joint equation models, copula regression modelling, generalized additive modelling and applications in wide range of applied areas. She has extensive experience with teaching applied statistics courses including regression models and computational data mining methods. Rosalba co-developed the GJRM package (former SemiParBIVProbit and SemiParSampleSel packages) in R since 2011 that led to over 60,000 downloads; the package is mainly addressed to a wide variety of practitioners that aims to model additive distributional joint (and univariate) regression models, with several types of covariate effects, in the presence of equations' errors association, endogeneity, non-random sample selection or partial observability.

Dr Pedro Rodrigues

Pedro is the module leader of the Strategic Business Analytics module he is one of the industry partners that designs and supervises the summer Applied Research Projects. He holds a PhD degree in Computer Science from Imperial College London. Pedro teaches applications of Machine Learning to key stakeholders from different backgrounds in Finance and regularly presents at reputable conferences and venues. Pedro is the CEO of Savvy Data Insights, where he leads an experienced and highly skilled team that help organisations solve their business problems using innovative solutions based on cutting edge technology and Artificial Intelligence/Machine Learning Algorithms. He is also part of the MSc in Business Analytics Industry Partners Programme that offers industry-based projects designed by Pedro that aim to enhance the experiential learning when the Term 3 Applied Research Project is developed. Such projects are directly supervised by the industry partner contact person(s).

Dr Simone Santoni

Simone Santoni is a Lecturer in Strategy at the Cass Business School, where he leads, among others, the Network Analytics and Data Visualisation teaching modules. He obtained a PhD in Organizations and Markets from the University of Bologna and refined his studies at Columbia University and New York University. Simone's research concentrates on the network foundations of organizations and markets―especially markets for culture and labour. Throughout the years, he has consulted for prominent organizations operating in the recording music industry, theatre, and contemporary art.

Dr Elizabeth Stephens

Dr. Elizabeth Stephens is the Founder & Managing Director of Geopolitical Risk Advisory, a consultancy that uses data analytics to advise clients on how geopolitical risks will impact upon their specific trading relationships and investments. For nine years prior to this, she was the Head of Credit & Political Risk Advisory at JLT Specialty where she provided corporate clients with strategic advice on the identification, management and mitigation of country risk. Elizabeth has a Ph.D. in International Relations from the London School of Economics and is a guest Lecturer at Cass Business School and Henley Business Schools, where she delivers Masters and Executive Education courses on Political Risk Management and Business Analytics. Elizabeth is also involved in teaching the Strategic Business Analytics module.  She is also part of the MSc in Business Analytics Industry Partners Programme that offers industry-based projects designed by Elizabeth that aim to enhance the experiential learning when the Term 3 Applied Research Project is developed. Such projects are directly supervised by the industry partner contact person(s).

Dr Rui Zhu

Rui is a Lecturer in Statistics and she is the Module Leader of the Machine Learning module. She obtained her PhD degree in statistics from University College of London and her research is in statistical learning, pattern recognition, high-dimensional data analysis and interdisciplinary applications for real-world problems. Rui’s research interests include classification and dimension reduction for high-dimensional data, distance metric learning and real-world applications, such as spectral data analysis, image quality assessment and hyperspectral image analysis.


How to apply

Documents required for decision-making

  • Transcript/interim transcript
  • Current module list (if still studying)
  • CV
  • Personal statement (500-600 words)

Documents also required (may follow at later date)

  • IELTS/GMAT reports
  • Two references, one of which MUST be an academic reference
  • Work experience is not a requirement of this course, applicants with in excess of three years of experience should consider the MBA programme
  • For a successful application to receive an unconditional status all documents must be verified, so an original or certified copy of the degree transcript must be sent by post to the Master's Programme Office, 106 Bunhill Row, London, EC1Y 8TZ, UK

We cannot comment on individual eligibility before you apply and we can only process your application once it is fully complete, with all requested information received.

Individual Appointments

If you would like to visit us to discuss your application please do arrange an individual appointment.

Terms and conditions

Students applying to study at Cass Business School are subject to City, University of London's terms and conditions.

Entry requirements

A UK upper second class degree or above, or the equivalent from an overseas institution, in a relevant subject is required.

Students with a degree that includes quantitative topics are sought and such degrees are: actuarial science, business, computer science, economics, engineering, finance, geography, mathematics, psychology, sociology, statistics or any other quantitative social science.


GMAT is recommended for students wishing to apply for this course.

English language requirements

If you have been studying in the UK for the last three years it is unlikely that you will have to take the test.

If you have studied a 2+2 degree with just two years in the UK you will be required to provide IELTS results and possibly to resit the tests to meet our requirements.


The required IELTS level is an average of 7.0 with a minimum of 6.5 in the writing section and no less than 6.0 in any other section.

Read more about English requirements


UK/EU/International £27,500 Tuition fees are subject to annual change

Fees in each subsequent year of study (where applicable) will be subject to an annual increase of 2%. We will confirm any change to the annual tuition fee to you in writing prior to you commencing each subsequent year of study for continuing students (where applicable).

Deposit: £2,000 (usually paid within 1 month of receiving offer and non-refundable unless conditions of offer are not met)

First installment: Half fees less deposit (payable during on-line registration which should be completed at least 5 days before the in-person ID–checks)
Second installment: Half fees (paid in January following start of course)

Information about Scholarships

Course information and statistics

average age of student body
females in 19/20 cohort
nationalities in 19/20 cohort