Statistics with Data Science MSc

Level: Postgraduate taught

Subject: Mathematics and Statistics

Year of entry: 2026

Study options

Mode of study

On campus

Full-time
  • MSc | 1 year | Start date: September 2026
Part-time
  • MSc | 2 years | Start date: September 2026

Key facts

School

School of Mathematics

College

College of Science and Engineering

Programme website
Study location

King's Buildings campus

Accreditation

Available

Apply now

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About the degree programme

In this digital and data-rich era, there is a high demand for statistics graduates from:

  • industry
  • the public sector
  • academia

However, the pool of graduates in this area is small. The recent growth of data science has highlighted the importance of statistics, with data analysis and results interpretation well-integrated into this newly recognised field.

This programme trains the next generation of statisticians to become expert data scientists with knowledge and experience of well-established methodologies and recent advances. The syllabus combines rigorous statistical theory with hands-on practical experience applying statistical models to data from various application areas.

In particular, the programme includes:

  • frequentist and Bayesian methods for advanced statistical modelling
  • computational statistics
  • generalised regression models
  • principles of statistically defensible data collection, management and curation

Graduates will be in high demand. We anticipate most students will be employed as statisticians for private and public institutions providing statistical advice and consultancy.

In this video our academic staff and students outline what to expect as part of a Masters in the area of Statistics.

One of the distinguishing features of this masters programme is the dissertation, where students will take on the role of a real data scientist. This involves tackling real-world data challenges and collaborating with industry experts to deliver impactful solutions. This opportunity empowers you to develop greater resilience and confidence, equipping you to excel across a wide range of industries.

David Aritonang MSc Statistics with Data Science, graduated 2025
David Aritonang, MSc Statistics with Data Science

Tuition fees

Tuition fees by award and duration

Tuition fees for full-time and part-time options are listed for one academic year.

Full-time
Part-time

Graduate discount

If you are a University of Edinburgh graduate, you will be eligible for a 10% discount on your tuition fees for this programme. You may also be eligible if you were a visiting undergraduate student.

Find out how to receive your graduate discount

Deposit

You do not have to pay a deposit to secure your place on this programme.

Costs

Accommodation and living costs

You need to cover your accommodation and living costs for the duration of your programme.

We estimate that you might spend £1,167 to £2,330 per month if you are a single student.

Living costs include:

  • food
  • utility bills
  • travel, clothes, books and stationery
  • recreational costs (for example, TV subscriptions and social events)

Living costs

Accommodation costs depend on where you live while studying and the type of accommodation you choose.

University postgraduate accommodation options and costs

Funding opportunities

Funding for postgraduate study is different to undergraduate study, and many students need to combine funding sources to pay for their studies.

Most students use a combination of the following funding to pay their tuition fees and living costs:

  • borrowing money
    • taking out a loan
    • family support
  • personal savings
  • income from work
  • employer sponsorship
  • scholarships

Explore sources of funding for postgraduate study

Search for other funding opportunities

You can find scholarships, bursaries and other funding you might be eligible for on our Scholarships and Student Funding site.

Postgraduate funding opportunities

These entry requirements are for the 2026-27 academic year and requirements for future academic years may differ. Entry requirements for the 2027-28 academic year will be published on 1 Oct 2026.

Qualifications

A UK 2:1 degree, or its international equivalent, in a numerate discipline such as mathematics, engineering, computer science, physical or biological sciences, economics or business. 
 
Your degree must have included substantial mathematics content, including calculus (including calculus of several variables), linear algebra, probability, statistics and statistical theory. Detailed information is available from the School of Mathematics website. 
 
You can increase your chances of a successful application by exceeding the minimum programme requirements.

International qualifications

To find international equivalent qualifications, select where you studied from the country or region list.

English language requirements

You must prove that your English language abilities are at a high enough level to study this degree programme.

This is the case for all applicants, including UK nationals.

You can meet our English language requirements with one of the following:

  • an English language test
  • a degree that was taught and assessed in English
  • certain professional qualifications

English language tests we accept

We accept any of the following English language tests, at the specified grade or higher:

  • IELTS Academic: total 6.5 with at least 6.0 in each component. We do not accept IELTS One Skill Retake to meet our English language requirements.
  • TOEFL-iBT (including Home Edition): total 92 with at least 20 in each component We do not accept TOEFL MyBest Score to meet our English language requirements.
  • C1 Advanced (CAE) / C2 Proficiency (CPE): total 176 with at least 169 in each component.
  • Trinity ISE: ISE II with distinctions in all four components.
  • Oxford ELLT: total 7 with at least 6 in each component.
  • Oxford Test of English Advanced: total 145 with at least 135 in each component.
How old your English language tests can be
Tests no more than two years old

The following English language tests must be no more than two years old on the 1st of the month in which your programme starts, regardless of your nationality:

  • IELTS Academic
  • TOEFL-iBT (including Home Edition)
  • Trinity ISE
  • Oxford ELLT
  • Oxford Test of English Advanced
Tests no more than three and a half years old

All other English language tests must be no more than three and a half years old on the 1st of the month in which your programme starts, regardless of your nationality.   

Degrees taught and assessed in English

We accept an undergraduate or postgraduate degree that has been taught and assessed in English in a majority English-speaking country, as defined by UK Visas and Immigration.

UKVI list of majority English speaking countries

We also accept a degree that has been taught and assessed in English from a university on our list of approved universities in non-majority English-speaking countries (non-MESC).

Approved universities in non-MESC

How old your degree can be

If you are not a national of a majority English-speaking country, then your degree must be no more than five years old on the 1st of the month in which your programme starts.

This time limit does not apply to your degree if you are a national of a majority English-speaking country.

Find out more about our English language requirements

Find out about other English language qualifications we accept, including professional qualifications.

English language requirements

What you will study

This programme involves two taught semesters of compulsory and option courses followed by your dissertation project.

Compulsory courses

Compulsory courses have previously included:

  • Bayesian Data Analysis
  • Bayesian Theory
  • Design and Sampling for Data Science
  • Extended Statistical Programming
  • Generalised Regression Models
  • Statistical Research Skills

Option courses

Optional courses have previously included:

  • Applied Machine Learning*
  • Biostatistics
  • Credit Scoring
  • Fundamentals of Operational Research
  • Fundamentals of Optimization
  • Incomplete Data Analysis
  • Large Scale Optimization for Data Science
  • Machine Learning in Python
  • Methods for Causal Inference*
  • Multivariate Data Analysis
  • Nonlinear Optimization
  • Python Programming
  • Simulation
  • Statistical Methodology
  • Stochastic Modelling
  • Targeted Causal Learning
  • Text Technologies for Data Science*
  • Theory of Statistical Inference
  • Time Series

*delivered by the School of Informatics

Find courses for this programme

Find out what courses you can study on this programme and how each of them are taught and assessed.

The courses on offer may change from year to year, but the course information will give you an idea of what to expect on this programme.

Full-time
Part-time

We link to the latest information available. This may be for a previous academic year and should be considered indicative.

Teaching and assessment

Assessment

Dissertation projects

The dissertation will take the form of two consultancy-style case projects in different application areas.

Each consultancy-style project will last five to six weeks and will take the form of a consultant-client style where an industrial client will present a problem to your class. Each student will then act as a consultant, addressing an aspect of the problem and presenting their conclusions to the client at the end of the five to six week period.

Learning outcomes

At the end of this programme you will have:

  • knowledge and understanding of statistical theory and its applications within data science
  • the ability to formulate suitable statistical models for new problems, fit these models to real data and correctly interpret the results
  • the ability to assess the validity of statistical models and their associated limitations
  • practical experience of implementing a range of computational techniques using statistical software R and JAGS

Support for your studies

Student Support Team

In the School of Mathematics, we have a dedicated Student Support Team consisting of six staff members.

You will have a Student Adviser who is your first point of contact during your time at the University of Edinburgh, and who is available to help and advise on a range of issues connected to your postgraduate study.

Study support will be provided by academics acting as Cohort Leads, with wider teaching teams, who will work with students to connect you with your programme of study and provide you with more specialist subject support.

Where you will study

Study location

Teaching for School of Mathematics courses will take place at the King's Buildings campus, usually in the James Clerk Maxwell Building (JCMB).

The MScHub in JCMB is specifically for School of Mathematics MSc students, and offers a dedicated space for studying and socialising, including its own kitchen facilities.

Academic facilities

Full details of the facilities available at King’s Buildings (including libraries, study spaces and catering outlets) are available on the College of Science and Engineering website:

Facilities at King's Buildings

Accreditation

This MSc is accredited by the Royal Statistical Society (RSS). Thus, this programme is recognised by RSS for the purpose of eligibility for the professional award of Graduate Statistician. The accreditation is based on the general depth, breadth, quality and foundation of the programme and its statistical content.

Career opportunities

Trained statisticians are in high demand both in public and private institutions. This programme will provide graduates with the statistical skills necessary to handle and analyse different forms of data, interpret the results and effectively communicate the conclusions.

Graduates will have a deep knowledge of the underlying statistical principles coupled with practical experience in implementing statistical techniques using standard software across a range of application areas, ensuring they are ideally placed for a range of different job opportunities.

The degree is also excellent preparation for further study in statistics or data science. Students have gone on to study their PhDs at highly ranked universities including Oxford and Edinburgh.

The School of Mathematics Business Development Team can also put students in touch with Edinburgh Innovations, who offer services for students interested in enterprise and entrepreneurship. There are several events during the year to explore and develop start-up ideas.

Edinburgh Innovations

Professional links

The School of Mathematics has connections with many of the following:

  • industrial partners
  • organisations
  • charities
  • government departments

As an MSc student in the School you will have opportunities to engage with these external organisations through:

  • regular employability events
  • careers workshops
  • our annual analytics challenge (whose recent partners have included Edinburgh Airport and the Data and Marketing Association)

You will also have the opportunity to work on an industry-based, consultancy-style dissertation project.

Recent partners for industry-based consultancy projects in the Statistics with Data Science MSc include:

  • Lloyds Banking Group
  • AzkoNobel
  • Public Health Scotland
  • Simply Business
  • Environment Agency

Further study

After completing this programme, you may wish to consider applying for a PhD or other research programme.

Applying for research degrees

Moving on to a PhD (advice from the University's Careers Service)

Graduate profiles

You can browse some recent Statistics graduate testimonials on our School website:

Student experience

Careers Service

Our Careers Service can help you to fully develop your potential and achieve your future goals. 

The Careers Service supports you not only while you are studying at the University, but also for up to two years after you finish your studies. 

With the Careers Service, you can: 

  • access digital resources to help you understand your skills and strengths
  • try different types of experiences and reflect on how and what you develop
  • get help finding work, including part-time jobs, vacation work, internships and graduate jobs
  • attend careers events and practice interviews
  • get information and advice to help you make informed decisions 

Visit the Careers Service website 

How to apply

You apply online for this programme. After you read the application guidance, select your preferred programme, then choose 'Start your application' to begin.

If you are considering applying to more than one programme, you should be aware that we cannot consider more than 3 applications from the same applicant.

When to apply

Due to high demand, the school operates a number of selection deadlines.

We strongly recommend you apply as early as possible. Applications may close earlier than the published deadlines if there is exceptionally high demand.

We may make a small number of offers to the most outstanding candidates on an ongoing basis. However, the majority of applications will be held until the advertised deadline.

We aim to make the majority of decisions within eight weeks of the selection deadline.

If we have not made you an offer by a specific selection deadline this means one of two things:

  • your application has been unsuccessful, in which case we will contact you to let you know
  • your application is still being considered, it will be carried forward for consideration in the next selection deadline, and we will be in touch once a decision is made

The final deadline may be extended if any places remain on the programme.

If the final deadline is extended, we encourage you to apply at least one month prior to entry so that we have enough time to process your application. If you are also applying for funding or will require a visa then we strongly recommend you apply as early as possible.

Selection deadlines

RoundApplication deadlineDecisions made or applications rolled to the next deadline
115 December1 March
231 March31 May
331 May31 July

When to submit your supporting documents

You must submit all supporting documents by the application deadline, or we will be unable to consider your application. Regardless of when you apply, you have 28 days from submitting your application to supply any supporting documents through the Application Hub, after which we will automatically reject your application.

Application fee

There is no fee to apply to this programme.

What you need to apply

As part of your online application, you will need to provide: 

You will also need to submit some or all of the following supporting documents:

When you start your application, you will be able to see the full list of documents you need to provide.

References

You must submit one reference with your application.

Apply

Select the award, duration and delivery mode you want to study. Then select the start date you want to apply for.

After you apply

Once you have applied for this programme, you will be able to track the progress of your application and accept or decline any offers.

Checking the status of your application

We will notify you by email once we have made a decision. Due to the large number of applications we receive, it might take a while until you hear from us.

Receiving our decision

What to do if you receive an offer:

What our students say

Student blogs

Learn about what life is like as a MSc student in the School of Mathematics by hearing from the people that have experienced it first-hand! Our student bloggers come from all across the world, and have studied on a variety of our MSc programmes.

Postgraduate blogs

Accommodation

We guarantee an offer of University accommodation for all new, single postgraduate taught students from outside the UK and new, single postgraduate research (typically PhD) students who:

  • apply for accommodation by 31 July in the year when you start your programme
  • accept an unconditional firm offer to study at the University by 31 July
  • study at the University for the whole of the academic year starting in September

University accommodation website

Accommodation guarantee criteria

We also offer accommodation options for couples and families.

Accommodation for couples and families

If you prefer to live elsewhere, we can offer you advice on finding accommodation in Edinburgh.

Accommodation information from the Edinburgh University Students' Association Advice Place

Societies and clubs

Our societies and sports clubs will help you develop your interests, meet like-minded people, find a new hobby or simply socialise.

Societies

Sport Clubs

The city of Edinburgh

Scotland's inspiring capital will form the background to your studies — a city with an irresistible blend of history, natural beauty and modern city life. 

Find out more about living in Edinburgh

Health and wellbeing support

You will have access to free health and wellbeing services throughout your time at university if you need them.

The support services we offer include: 

  • a student counselling service
  • a health centre (doctor's surgery)
  • support if you're living in University accommodation
  • dedicated help and support if you have a disability or need adjustments

Health and wellbeing support services 

Disability and Learning Support

General enquiries

Admissions
School of Mathematics
James Clerk Maxwell Building
The King's Buildings Campus
Edinburgh
EH9 3FD

futurestudents@ed.ac.uk

Academic contact

Dr Ioannis Papastathopoulos

Programme Director

Contact details

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