Statistics with Data Science MSc

Level: Postgraduate taught

Subject: Mathematics and Statistics

Year of entry: 2027

Study options

Mode of study

On campus

Full-time
  • MSc | 1 year | Start date: September 2027
Part-time
  • MSc | 2 years | Start date: September 2027

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 a digital and data-rich world, organisations across industry, the public sector and research need people who can combine programming with statistical analysis, data management and careful interpretation to turn complex data into usable evidence.

This programme combines rigorous statistical training with practical data science. You will study frequentist and Bayesian methods, computational statistics, regression modelling, and statistically defensible approaches to data collection, management and curation. You will also develop practical skills in programming, data analysis and communication, so that you can turn complex data into clear, usable evidence.

A major feature of the programme is its applied, consultancy-style dissertation format. In the summer, you will complete two back-to-back case projects in different application areas. This gives you the chance to work on realistic briefs, build breadth across more than one sector, and develop the confidence, resilience and communication skills needed in professional data science roles.

Edinburgh offers a strong environment for this training through the School of Mathematics, a broad optional-course portfolio, and links with external organisations across industry and the public sector.

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

Study options

This programme can be studied full-time over 1 year or part-time over 2 years.

Part-time study

If you study part-time, you will take half of the taught credits in your first year, and the other half in your second year. You will complete the final project full-time in the summer at the end of your second year.

Our large course offering means that taught courses have contact times throughout the week, and you are expected to be on campus during these times.

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 will need to pay for your accommodation and living costs (such as rent, food and utility bills) for the duration of your programme.

For 2026-2027, we estimate that it will cost an average of £18,504 each year (£1,542 each month) to live in Edinburgh as a postgraduate.

The exact amount you spend will depend on different factors, especially the accommodation you choose.

Living costs: estimates explained 

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

The University is offering an international scholarship for the most academically gifted postgraduate taught (PGT) masters students applying from India. These awards, which cover £5,000 towards tuition fees for PGT masters students studying on campus will be tenable for the first year of study only.

Value: £5,000
View details: Find out more about the India Merit Scholarships

The College of Science and Engineering is offering an international scholarship for the most academically gifted postgraduate taught (PGT) masters students applying from France, Germany and Spain. These awards, which cover £10,000 towards tuition fees for PGT masters students studying on campus will be tenable for the first year of study only. 

Value: £10,000
View details: Find out more about the European Merit Scholarships

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 2027-28 academic year and requirements for future academic years may differ. Entry requirements for the 2028-29 academic year will be published in early Oct 2027.

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 equivalent 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 (restrictions apply)
  • a degree that was taught and assessed in English (restrictions apply)
  • 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) before 21 January 2026: total 92 with 23 in each component. We do not accept TOEFL MyBest Score to meet our English language requirements.
  • TOEFL-iBT (including Home Edition) from 21 January 2026: total 4.5 with at least 4.5 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.
  • Oxford ELLT: total 7 with at least 6 in each component. We do not accept Oxford ELLT Skill Retake to meet our English language requirements.
  • 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)
  • 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

The MSc comprises 180 credits. You will complete 120 taught credits and a 60-credit dissertation project.

Across two taught semesters, you will build a strong foundation in modern statistics and data science. You will study statistical modelling, programming, regression, data design and related methods, and learn how to use them responsibly across a range of real application areas.

In the summer, you will complete a distinctive dissertation format based on two back-to-back consultancy-style case projects. This gives you the chance to work as a data scientist on real or realistic briefs, applying statistical methods, communicating conclusions and producing decision-ready outputs.

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

Option 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

Teaching

Teaching methods include lectures, practical classes, workshops, coursework, independent study and dissertation supervision.

The programme combines mathematical and statistical foundations with hands-on data analysis. You will work with real data, implement methods in standard software, evaluate model performance and limitations, and present your results clearly.

Assessment

Assessment across the programme includes written examinations, coursework, programming exercises, practical tasks, reports and dissertation project work.

Dissertation projects

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

Each project typically lasts five to six weeks and follows a consultant-client model. An industrial or external-style client presents a problem to the class, and you work on an aspect of that problem before presenting your conclusions at the end of the project.

This is one of the programme's most distinctive features and a major opportunity to build employability, confidence and applied problem-solving skills.

Learning outcomes

At the end of this programme you will be able to:

  • demonstrate understanding of statistical theory and its applications within data science
  • formulate suitable statistical models for new problems, fit them to real data, and interpret the results appropriately
  • assess the validity of statistical models and recognise their limitations
  • implement computational techniques using statistical software including R and JAGS
  • analyse data from different application areas and communicate conclusions clearly
  • apply statistical and data science methods to practical problems through consultancy-style project work

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). This means the programme is recognised by the RSS for the purpose of eligibility for the professional award of Graduate Statistician.

The accreditation reflects the depth, breadth, quality and statistical foundation of the programme.

Career opportunities

Graduates from this programme will be prepared for work wherever strong statistical reasoning and data analysis are needed.

Roles may include:

  • Statistician
  • Data Scientist
  • Data Analyst
  • Biostatistician
  • Risk Analyst
  • Public-sector Analyst
  • Quantitative Consultant
  • Research Data Scientist

You may be particularly well suited to sectors such as healthcare, finance, government, consulting, insurance, technology and other data-intensive industries.

The programme develops both technical and professional skills: statistical modelling, data analysis, programming, interpretation, communication and consultancy-style working. These are valuable in a wide range of public and private institutions.

The degree is also excellent preparation for further study in statistics or data science. Students have gone on to study for 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, which supports enterprise and entrepreneurship activity.

Edinburgh Innovations

Professional links

The School of Mathematics has connections with industrial partners, organisations, charities and government departments.

As an MSc student in the School, you will have opportunities to engage with external organisations through regular employability events, careers workshops, and the 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 - "Network security: Exploring the use of  autoencoders and variational autoencoders for anomaly detection in cyber security"
  • Public Health Scotland - "Understanding the impact of age demographics on hospital admissions in Scotland"
  • Environment Agency - "Temporal trends in freshwater macroinvertebrate abundance: combining numerical and categorical  data using mgcv's grouped family (gfam)"
  • Space Intelligence - "Filling the gaps: Using synthetic aperture radar data to reconstruct multispectral images"
  • Simply Business - "Property insurance risk assessment: using public data to estimate building features that affect insurance value"
  • Xi Engineering - "Removing seismic noise (background) from wind turbine impact measurement datasets"

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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