About this course
Develop the specialist skills and knowledge to carry out official statistics work on this flexible Data Analytics for Government MSc at the University of Southampton. Learn the survey methods and social data analysis skills to work for the UK government, an overseas government, or a non government organisation conducting large-scale statistical or analytical work.
This UK social data science master’s course is ideal if you are currently working in official statistics or the Government Statistical Service (GSS).
You'll strengthen and update your professional skills and knowledge of survey methods, data science and data analysis.
Compulsory topics you’ll cover include:
- the use of statistical software, such as R and Python, for data manipulation, analysis and simulation
- dealing with administrative and big data sources
- the scope and organisation of official statistics
- statistical acts and codes and practice
You’ll be able to fit the course to your personal interests or career plans through a range of specialist optional modules.
Flexible study
If you prefer, you can apply to study this course as:
a part-time master's - study the same course content over 2-5 years
You can also choose to study any of the course modules as part of continuing professional development (CPD). If you later apply for the part-time master's, you can transfer up to 4 modules onto your academic record as part of the Recognition of Prior Learning scheme.
Your modules and fees may vary if you choose a different study option.
We regularly review our courses to ensure and improve quality. This course may be revised as a result of this. Any revision will be balanced against the requirement that the student should receive the educational service expected. Find out why, when, and how we might make changes.
Our courses are regulated in England by the Office for Students (OfS).
Course lead
Your course leader is Dr Angela Luna Hernamdez.
Learn more about these subject areas
Course location
This course is based at Highfield.
Awarding body
This qualification is awarded by the University of Southampton.
Entry requirements
You’ll need a 2:1 in a subject with some statistical methods content, such as:
- geography
- psychology
- population sciences
- economics
- econometrics
- statistics
- maths
Find the equivalent international qualifications for your country.
If your degree doesn’t have any statistical content, we’ll ask you to show that you have the necessary background knowledge to the level of the Royal Statistical Society Higher Certificate in Statistics.
You should be currently employed in official statistics, but previous professional experience might be taken into account.
If you’re successful in your application to join this course, we'll ask you to attend an introductory revision module covering basic maths and statistics before the course starts.
English language requirements
If English is not your first language, you must show that you can use English to the level we require. Visit our English language pages to find out which qualifications we accept and how you can meet our requirements.
If you are taking the International English Language Testing System (IELTS), you must get at least the following scores:
IELTS score requirements
- overall score
- 6.5
- reading
- 6.0
- writing
- 6.0
- speaking
- 6.0
- listening
- 6.0
If you do not meet the English language requirements through a test or qualification, you may be able to meet them by completing one of our pre-sessional English programmes before you start your course.
Pre-masters
If you don’t meet the academic requirements, you can complete a pre-master's programme through our partnership with OnCampus. Learn more about the programmes available.
Recognition of professional experience
If you don't have the exact entry requirements, but you have significant work experience in this sector we’ll assess your relevant professional experience, your subject knowledge and your aptitude for learning.
Your application will be considered on individual merit and you may be asked to attend an interview.
Got a question?
Please contact us if you're not sure you have the right experience or qualifications to get onto this course.
Email: enquiries@southampton.ac.uk
Tel: +44(0)23 8059 5000
Course structure
Part-time study
If you choose to study the course over 2 to 5 years, you must:
- complete 2 modules each year
- complete all modules by the end of semester 2 in your fourth year of registration
Your optional modules take place in 1 week slots throughout the year. We rotate these modules over a 4 year cycle, so not all optional modules are available in each year.
Full-time study
If you choose to study full-time over 1 year you'll focus on the taught part of your course for the first 8 months (semesters 1 and 2). For the remainder of the degree, you’ll work independently on your dissertation.
Compulsory modules are available each year. Only the scheduled optional modules for a particular year will be available.
Want more detail? See all the modules in the course.
Modules
The modules outlined provide examples of what you can expect to learn on this degree course based on recent academic teaching. As a research-led University, we undertake a continuous review of our course to ensure quality enhancement and to manage our resources. The precise modules available to you in future years may vary depending on staff availability and research interests, new topics of study, timetabling and student demand. Find out why, when and how we might make changes.
For entry in academic year 2026 to 2027
Year 1 modules
You must study the following modules :
Data Mining
New sources of data in a wide range of formats contain valuable information, but extracting this information is often challenging using traditional tools. This module introduces modern techniques for analysing such data and demonstrates how they may be pu...
Data Visualisation
Data visualisation is the process of summarising and communicating the information in a dataset through graphics. This course examines what makes good visualisations, and how this depends on the audience and purpose of the visualisation and the type of da...
Dissertation
This module will provide you with guidance and support throughout the writing of your dissertation. From discussing your initial ideas of your dissertation through the process of actually writing the document, this module will provide you with the informa...
Elements of Statistics and Data Science
The aim of this module is to provide a foundation for the more advanced modules in the programme. The first part of the module will provide a revision of the basic elements of statistics that will be relevant to the programme, such as expectation and ...
Generalised Linear Models
This module aims to introduce students to a wide range of statistical models grouped by the unifying theory of generalized linear models: linear, logistic, multinomial, cumulative ordinal and Poisson regression, as well as log-linear models are presented,...
Machine Learning
The module aims to equip students with the necessary foundations to make practical and effective use of machine learning methods on complex datasets. This course uses R and is delivered as an intensive one-week module for the MSc in Data Analytics for Gov...
Research Communication Skills
This modules teaches the basic principles of research communication skills. It covers essential scientific writing skills including, organization of written material, presentation of quantitative information, citation and referencing, and academic integri...
Statistical Programming in R
This module aims to give students a grounding in the use of statistical software for data manipulation, analysis and simulation in R.
Statistics in Government
The module provides an overview of issues and ideas concerning the scope and organisation of Official Statistics and its processes and products, including Statistical Acts and Codes of Practice. The module provides a general foundation for the more det...
You must also choose from the following modules :
Compensating for Non-Response
The aim of this module is to develop students’ understanding of the principles and methods used to compensate for non-response following survey data collection and to enable them to design a strategy for compensating for non-response in a particular surve...
Complex Survey Data Analysis
The aim of this module is to provide an introduction to the finite-population inference and modelling approaches for survey data.
Demographic Methods 1
This Module provides an introduction to the technical basis of demography. It focuses on concepts and methods underpinning demographic analysis and provides a practical introduction for those professionally engaged with demographic work (in government dep...
Demographic Methods 2
The module will cover a range of more advanced methods of demographic analysis, including multiple decrement life tables, health expectancies, an introduction to event history analysis, the use of type 1 and type 2 rates in demography and sources of bias ...
Design of Experiments
A well-designed experiment is an efficient way of learning about the world. Typically, an experiment may involve varying several factors and observing the value of a response at settings of combinations of values of these factors. The mathematical challen...
Epidemiological Methods
This module introduces students to the main concepts involved in epidemiological analyses. The main epidemiological study designs are introduced and two lectures focus on methods used to analyse case-control studies whilst another two focus on cohort stu...
Evaluation and Monitoring
The aim of this module is to develop students' understanding of the nature of studies to monitor and evaluate intervention programmes, using examples from Government and other related areas. There is a particular focus on the contribution of statistical m...
Further topics in statistical modelling
This module provides a broad introduction to more advanced regression methods such as multilevel models, non-parametric and penalised regression and Generalized Additive models. The module assumes that students are familiar with basic regression techniqu...
Index Numbers
The aim of this module is to provide an introduction to the theory and practice of price index numbers.
Key Topics in Social Science: Measurement and Data
This module introduces key sources of social science data (both UK and non-UK), and the measurement of key concepts using these data, within a range of substantive areas. In doing so it focuses on the analysis of a number of fundamental social issues – in...
Likelihood and Bayesian Inference
This module develops methods for conducting inference about parametric statistical models. The techniques studied are general and applicable to a wide range of statistical models, including simple models for identically distributed responses and regressio...
Population, Poverty & Policy
During the module you will develop your key skills in: 1. Understanding and exploring the associations between population, poverty and policy issues in a range of countries and setting 2. Analysing complex information and producing well-argued and s...
Qualitative Research Methods 1
The module is aimed at enabling you to understand the principles of qualitative methods and analysis, and equipping you to apply qualitative research methods in practice. The module assumes no previous knowledge of either NVivo or qualitative analysis so...
Small Area Estimation
The aim is to provide you with an overview and a broad understanding of methods of small area estimation, their motivation and applications.
Statistical Disclosure Control
The module covers methods of disclosure control for tabular data and microdata, and how the utility of the resulting data is traded off against the risk of disclosure.
Statistical Genetics
Statistical genetics has played a pivotal role in the discovery of genes that cause disease in humans. This module introduces the basic concepts and terms in genetics and demonstrates the use of statistical models to identify disease genes in humans.
Statistical programming in Python
This module aims to give students a grounding in the use of statistical software for data manipulation and analysis in Python.
Survey Design and Data Quality
Students taking this module will gain first-hand experience in the design and implementation of surveys and how to investigate and explore issues with data quality from these surveys.
Survival Models
This module introduces some of the fundamental ideas and issues of lifetime and time-to-event data analysis, as used in actuarial practice, biomedical research and demography Co-Requisite: MATH6122
Time Series Analysis
This module will provide an introduction to time series models in common use and their use for predicting future observations and/or estimating unobservable components like trend and seasonal effects.
Understanding Population Change
This module is an introduction to the substantive concepts of demography, how populations change and grow or shrink, and the transitions that populations make in various stages of their development. An introduction to the past, present and future world po...
Learning and assessment
Learning
The learning activities for this course include:
- lectures
- seminars
- discussions
- group work
- project work
- independent study
Assessment
We’ll assess you through:
- coursework
- written exams
- a dissertation
Dissertation
You’ll research and write a 15,000 to 20,000-word dissertation on a subject of your choice, to be agreed with your supervisor.
Dissertations usually involve the application of methods you’ve learned during the taught part of the course. They’re a chance for you to develop your research skills and show in-depth knowledge of a particular topic.
You’ll have regular support meetings with your supervisor throughout the process.
Academic Support
You’ll be assigned a personal academic tutor and have access to a senior tutor.
Careers and employability
Employability skills
This degree will allow you to develop and evidence subject-specific and targeted employability skills. This includes the required skill set for a range of future careers, further study, or starting your own business.
The skills you can expect to focus on and gain from this course include:
- Research
- Critical thinking
- Self-management
- Communication
- Problem solving
The employability and enterprise skills you'll gain from this course are reflected in the Southampton skills model. When you join us you'll be able to use our skills model to track, plan, and benefit your career development and progress.
Download skills overview
Career pathways
Graduates commonly work in a range of organisations or sectors including:
local and national government,
Research,
Business consultancy,
IT,
Defence,
Finance.
- Data analyst
- Data scientist
- Machine learning engineer
- Big data architect
- Business Intelligence analyst
- Information strategist
- Quantitative analyst
- Marketing analyst
- Operations analyst
- Consultant
- Data officer
- Data engineer
- Data analyst
- Actuary
- Business analyst
- Consultant
- Data engineer
- Data scientist
- Head of revenue analysis
- Data architect
- Economic advisor
- Research scientist
Job prospects for MSc Data Analytics for Government part time graduates
*Example graduate job titles and job prospect statistics taken from The Graduate Outcomes Survey, which gathers information about the activities and perspectives of graduates 15 months after finishing their course.
Work experience opportunities
Choosing to do work experience is a great way to enhance your employability, build valuable networks, and evidence your potential. Learn about the different work and industry experience options at Southampton.
Careers services and support
We are a top 20 UK university for employability (QS Graduate Employability Rankings 2022). Our Careers, Employability and Student Enterprise team will support you. This support includes:
- work experience schemes
- CV and interview skills and workshops
- networking events
- careers fairs attended by top employers
- a wealth of volunteering opportunities
- study abroad and summer school opportunities
We have a vibrant entrepreneurship culture and our dedicated start-up supporter, Futureworlds, is open to every student.
Your career ideas and graduate job opportunities may change while you're at university. So it is important to take time to regularly reflect on your goals, speak to people in industry and seek advice and up-to-date information from Careers, Employability and Student Enterprise professionals at the University.
Fees, costs and funding
Tuition fees
Fees for a year's study:
- UK students pay £14,300.
- EU and international students pay £26,200.
Deposit
If you're an international student on a full-time course, we'll ask you to pay £2,000 of your tuition fees in advance, as a deposit.
Your offer letter will tell you when this should be paid and provide full terms and conditions.
Find out about exemptions, refunds and how to pay your deposit on our tuition fees for overseas students page.
What your fees pay for
Your tuition fee covers the full cost of tuition and any exams. The fee you pay will remain the same each year from when you start studying this course. This includes if you suspend and return.
Find out how to pay your tuition fees.
Accommodation and living costs, such as travel and food, are not included in your tuition fees. There may also be extra costs for retake and professional exams.
Explore:
10% alumni discount
If you’re a graduate of the University of Southampton, you could be eligible for a 10% discount on your postgraduate tuition fees.
Postgraduate Master’s Loans (UK nationals only)
This can help with course fees and living costs while you study a postgraduate master's course. Find out if you're eligible.
ONS Data Science Campus sponsorship
If you're working as an analyst in the public sector, you might be eligible for sponsorship by the ONS Data Science Campus.
Successful students are expected to act as data science ambassadors and evangelists across government.
Find out more on the MSc in Data Science Campus website.
Southampton Economic, Social and Political Sciences Postgraduate International Scholarship
A scholarship of £3,000 is available to international students studying for a postgraduate master’s in Economic, Social and Political Sciences.
Find out more about the Southampton Economic, Social and Political Sciences International Scholarship, including eligibility and conditions.
Other postgraduate funding options
A variety of additional funding options may be available to help you pay for your master’s study. Both from the University and other organisations.
Funding for EU and international students
Find out about funding you could get as an international student.
How to apply
- Use the blue 'apply for this course' button on this page to take you to our postgraduate admissions system.
- Create an account which gives you access to your own application portal. .
- Search for the course you want to apply for.
- Complete the application form and upload any supporting documents.
- Submit your application.
For further details of our admission process, read our step by step guide to postgraduate taught applications.
Application deadlines
- International applicants: Wednesday 26 September 2026, midday, UK time
- UK applicants: Wednesday 9 September 2026, midday, UK time
Supporting information
When you apply you’ll need to submit a personal statement explaining why you want to take the course.
You’ll need to include information about:
- your knowledge of the subject area
- why you want to study a postgraduate qualification in this course
- how you intend to use your qualification
References are not required for this programme.
Please include the required paperwork showing your first degree and your IELTS English language test score (if you are a non-native English speaker) with your application. Without these, your application may be delayed.
What happens after you apply
You'll be able to track your application through our online Applicant Record System.
We will aim to send you a decision 6 weeks after you have submitted your application.
If we offer you a place, you will need to accept the offer within 30 working days. If you do not meet this deadline, we will offer your place to another applicant.
Unfortunately, due to number of applications we receive, we may not be able to give you specific feedback on your application if you are unsuccessful.
Equality and diversity
We treat and select everyone in line with our Equality and Diversity Statement.
Got a question?
Please contact us if you're not sure you have the right experience or qualifications to get onto this course.
Email: enquiries@southampton.ac.uk
Tel: +44(0)23 8059 5000
