MSc Operations Research & Analytics

  • Graduate taught
  • Department of Mathematics
  • Application code G2U1
  • Starting 2020
  • UK/EU full-time: Closed
  • Overseas full-time: Closed
  • Location: Houghton Street, London

The MSc Operations Research & Analytics provides you with the skills needed to apply mathematical methods to real-world analytics problems faced by companies, governments, and other institutions.

With study in practice and theory, you will gain deep insight into analytics problems. On the practical side, you will learn how to model a range of real-world problems using optimisation, simulation, and statistics, with specialist software taught with accompanying computer lab sessions. On the theoretical side, you will learn to recognise canonical underlying mathematical problems, and how to solve them with state-of-the-art methods.

You will also have the opportunity to undertake a Project in Operations Research & Analytics, working in a consultancy role in a host organisation, where you will turn a real problem faced by the organisation into a mathematical model whose solution provides tangible benefit. Alternatively, you may choose to write a dissertation, supervised by a faculty member.

The programme is designed for students with strong quantitative backgrounds wishing to deepen and broaden their mathematical knowledge while gaining applicable skills in high demand in the marketplace. 

Teaching and learning in Michaelmas Term 2020 
Information on how LSE will deliver teaching and learning in Michaelmas term can be found here.

Programme details

Key facts

MSc Operations Research & Analytics
Start date 28 September 2020
Application deadline None – rolling admissions. However please note the funding deadlines
Duration 12 months full-time only
Applications 2018 350
Intake 2018 30
Tuition fee UK/EU: £24,264
Overseas: £24,264
Financial support Graduate support scheme (deadline 27 April 2020)
Minimum entry requirement 2:1 degree or equivalent in a relevant discipline, normally including calculus, linear algebra and statistics. Appropriate work experience will also be considered
GRE/GMAT requirement Not mandatory but recommended
English language requirements Standard (see 'Assessing your application')
Location  Houghton Street, London

For more information about tuition fees and entry requirements, see the fees and funding and assessing your application sections.

Entry requirements

Minimum entry requirements for MSc Operations Research & Analytics

An upper second class honours (2:1) degree in a relevant discipline (or equivalent). Students should normally have taken university courses including calculus, linear algebra, and statistics. Appropriate work experience will also be considered.

Competition for places at the School is high. This means that even if you meet our minimum entry requirement, this does not guarantee you an offer of admission.

If you have studied or are studying outside of the UK then have a look at our Information for International Students to find out the entry requirements that apply to you.

Assessing your application

We welcome applications from all suitably qualified prospective students and want to recruit students with the very best academic merit, potential and motivation, irrespective of their background.

We carefully consider each application on an individual basis, taking into account all the information presented on your application form, including your:

- academic achievement (including predicted and achieved grades)
- statement of academic purpose
- two academic references
- CV

See further information on supporting documents

You may also have to provide evidence of your English proficiency, although you do not need to provide this at the time of your application to LSE.  See our English language requirements.

When to apply

Applications for this programme are considered on a rolling basis, meaning the programme will close once it becomes full. There is no fixed deadline by which you need to apply, however to be considered for any LSE funding opportunity, you must have submitted your application and all supporting documents by the funding deadline. See the fees and funding section for more details. 

Programme structure and courses

You will take three compulsory courses and will choose courses from a range of options within the Department and across other relevant departments, including Management and Statistics. 

(* denotes half unit) 

Fundamentals of Operations Research*
Introduces a range of Operations Research techniques including linear programming, the simplex method and duality, Markov chains, queueing theory and birth and death processes, inventory models and dynamic programming.

Modelling in Operations Research*
Provides hands-on training in the art of converting real-world problems to optimisation and simulation models, inputting the models into specialist software, solving the optimisation problem or exercising the simulation model, and deriving applicable conclusions about the original problem.

Data Analysis and Statistical Methods*
Studies common techniques of statistical inference, together with theoretical justification. The techniques are then applied to linear and logistic regression and basic time series models. Statistical software R constitutes an integral part of the course and provides hands-on experience of data analysis. 

Project in Operations Research & Analytics
A project in a host organisation taking a consultancy role.
Dissertation in Operations Research & Analytics
An independent research project of 10,000 words on an approved topic of your choice.

Courses to the value of one and a half units from a range of options.

For the most up-to-date list of optional courses please visit the relevant School Calendar page.

You must note however that while care has been taken to ensure that this information is up to date and correct, a change of circumstances since publication may cause the School to change, suspend or withdraw a course or programme of study, or change the fees that apply to it. The School will always notify the affected parties as early as practicably possible and propose any viable and relevant alternative options. Note that that the School will neither be liable for information that after publication becomes inaccurate or irrelevant, nor for changing, suspending or withdrawing a course or programme of study due to events outside of its control, which includes but is not limited to a lack of demand for a course or programme of study, industrial action, fire, flood or other environmental or physical damage to premises.

You must also note that places are limited on some courses and/or subject to specific entry requirements. The School cannot therefore guarantee you a place. Please note that changes to programmes and courses can sometimes occur after you have accepted your offer of a place. These changes are normally made in light of developments in the discipline or path-breaking research, or on the basis of student feedback. Changes can take the form of altered course content, teaching formats or assessment modes. Any such changes are intended to enhance the student learning experience. You should visit the School’s Calendar, or contact the relevant academic department, for information on the availability and/or content of courses and programmes of study. Certain substantive changes will be listed on the updated graduate course and programme information page.

Teaching and assessment

Contact hours and independent study

Teaching will combine traditional lectures with seminars and/or computer sessions. Several of the courses (including two of the three compulsory ones) will involve training in a programming language or use of specialised computational tools. These parts of those courses will have accompanying computer lab sessions in which students will actively develop their programming skills by applying them to a range of problems in OR. 

The MSc offers the option of taking one course from the Department of Management. These courses provide further exposure to management issues, viewed from qualitative and/or quantitative perspectives. 

You are required to do either a Project in Operations Research & Analytics or a Dissertation in Operations Research & Analytics (both during the summer). The Project involves work in a host organisation (in business, government, health, or a social non-profit organisation), in a consultancy role, typically turning a real problem faced by the organisation into a mathematical model whose solution provides tangible benefit. You will be marked on a project report. The Dissertation requires study of an area of research, or an application of advanced techniques, and a report of findings. 

Within your programme you will take a number of courses, including half unit courses and full unit courses, to a total of 4 units. In half unit courses, on average, you can expect 35 contact hours in total and for full unit courses, 40-60 contact hours in total. This includes sessions such as lectures, seminars or workshops. Hours vary from course to course and you can view indicative details in the Calendar within the Teaching section of each course guide.

You are also expected to complete independent study outside of class time. This requires you to manage the majority of your study time yourself, reading, thinking, solving problems, doing software exercise, and undertaking research.

Teaching methods

LSE is internationally recognised for its teaching and research and therefore employs a rich variety of teaching staff with a range of experience and status. Courses may be taught by members of faculty, such as assistant, associate, and full professors. Many departments now also employ guest teachers and visiting members of staff, LSE teaching fellows, and graduate teaching assistants who are usually doctoral research students and in the majority of cases teach on undergraduate courses only. You can view indicative details for the teacher responsible for each course in the relevant course guide.


All taught courses are required to include formative coursework which is unassessed. It is designed to help prepare you for summative assessment which counts towards the course mark and to the degree award. LSE uses a range of formative assessment, such as essays, problem sets, case studies, reports, quizzes, mock exams and many others. Summative assessment may be conducted during the course or by final examination at the end of the course. An indication of the formative coursework and summative assessment for each course can be found in the relevant course guide.

Academic support

You will also be assigned an academic mentor who will be available for guidance and advice on academic or personal concerns.

There are many opportunities to extend your learning outside the classroom and complement your academic studies at LSE. LSE LIFE is the School’s centre for academic, personal and professional development. Some of the services on offer include: guidance and hands-on practice of the key skills you will need to do well at LSE: effective reading, academic writing and critical thinking; workshops related to how to adapt to new or difficult situations, including development of skills for leadership, study/work/life balance and preparing for the world of work; and advice and practice on working in study groups and on cross-cultural communication and teamwork.

LSE is committed to enabling all students to achieve their full potential and the School’s Disability and Wellbeing Service provides a free, confidential service to all LSE students and is a first point of contact for all disabled students.

Preliminary reading

You are not  required to do any preliminary reading in advance of this programme, but if you wish to read some material before arriving, we can make a few suggestions. 

If you do not have experience of  computer programming, you could learn the language R, which you will use in ST447 Data Analysis and Statistical Methods. Once you learn any language it is easy to learn others, and programming will be useful in your career. Programming will also give you a sense of what computers can and cannot do, that will be useful in all algorithmic courses. Good starting points are Introductory Statistics with R by Peter Dalgaard, and the Coursera course.

Linear algebra plays a major role in several key courses and in the field of OR generally. It is expected that you are comfortable with the basic notions (linear independence, rank, determinants, solutions of systems of equations, eigenvalues and eigenvectors). These will not be reviewed in the course; you can review this material independently. There are many good textbooks to choose from; a suitable one is Linear Algebra by Martin Anthony and Michele Harvey. 

Student stories

To read all our Alumni Stories, see our webpage here.

Philipp Loick - MSc Operations Research & Analytics 2017-18

Philipp Loick

Having a background in finance and economics, I aimed for a Masters programme where I could develop mathematical and programming skills to solve industry problems in operations research and data science. Enrolling in the Operations Research and Analytics programme at LSE was the right choice for this goal.

The programme features a diverse student body with the majority of students having majored in mathematics with some engineering and finance students. Even though only a one-year programme, the programme achieved a good balance between theoretical foundations and industry applications and allowed us to study topics such as combinatorial optimization, advanced statistics or algorithmic techniques for data mining.

The high academic level and relevance of the programme is due to the academic staff, who have excellent academic credentials, partially have worked for renowned industry companies and are well connected in the academic community. Graduating from the programme, I had an offer from BCG Gamma, the advanced analytics team of BCG, which I rejected for a PhD in discrete mathematics.


Alexander Saftschuk - MSc Operations Research & Analytics 2017-18

Alexander Saftschuk

I came to the LSE with the main goal of improving my quantitative problem-solving skills, and subsequently landing a job in investment banking. The School and societies provided extremely good network opportunities, which really helped to land the job that I aimed at. After only two months at the LSE I landed a job offer with one of the top global investment banks. However, upon finishing the Operations Research & Analytics programme I quickly realised that I would rather pursue a career in data science, and once again the university's reputation opened doors for me last minute. Currently I work as a Data Analyst in the Telenor Digital data science team in Norway. There I code various machine learning algorithms in R, all of which I have all learned during this degree. 

Overall I can say that coming from a non-quantitative, business background I have learned more in this one-year Masters than I did in my entire three years of my bachelor degree. The programme was challenging but manageable. In particular, I highly appreciated how much face time I received from all of my professors, as well as the professor who supervised my thesis. The decision to come to the LSE and studying Operations Research & Analytics was one of the best I have made so far and I can highly recommend LSE and the degree. 


Kate Lavrinenko - MSc Operations Research & Analytics 2017-18

Studying this Masters was my third MSc, after studying Applied Mathematics and Economics, four years of experience in Economics and Finance, moving country, two kids, and four years at home with them. It was a challenging experience to find myself among young, inspired and able students from around the world. It also took some time to get used to the pace of study, and to network with people and share skills and knowledge. I needed some psychological help at the start of the journey and I had an opportunity to get it at LSE, which makes me feel grateful. 

I liked that the programme was flexible in what courses you could choose in order to make it fit your personal interests and academic goals. I encourage students to research and think hard about their course choices before starting the programme. Also, it is useful to have an understanding of which direction you wish to head in (e.g. academic or business) so you can utilise LSE’s resources properly. 

I found the careers events to be very valuable in my experience here. For example, I met a member of the Data Science team from Deloitte and after many rounds and following my MA425 Project there in the summer, I found myself with a full time job after finishing the course.

I enjoyed my journey, my job, and my experience with LSE. Whenever I get a new research heavy task, I start dreaming whether I could eventually turn it into a PhD, so my journey is not over.


This programme is ideal preparation for a range of careers in quantitative positions in consultancy, management, finance, government and business, anywhere in the world.

Further information on graduate destinations for this programme

Support for your career

Many leading organisations give careers presentations at the School during the year, and LSE Careers has a wide range of resources available to assist students in their job search. Find out more about the support available to students through LSE Careers.

Fees and funding

Every graduate student is charged a fee for their programme.

The fee covers registration and examination fees payable to the School, lectures, classes and individual supervision, lectures given at other colleges under intercollegiate arrangements and, under current arrangements, membership of the Students' Union. It does not cover living costs or travel or fieldwork.

Tuition fees 2020/21 MSc Operations Research & Analytics

UK/EU students: £24,264
Overseas students: £24,264

Fee status

For this programme, the tuition fee is the same for all students regardless of their fee status. 
However any financial support you are eligible for will depend on whether you are classified as a Home (UK/EU) or Overseas student, otherwise known as your fee status. LSE assesses your fee status based on guidelines provided by the Department of Education.

Fee reduction

Students who completed undergraduate study at LSE and are beginning taught graduate study at the School are eligible for a fee reduction of around 10 per cent of the fee.

Scholarships and other funding

The School recognises that the cost of living in London may be higher than in your home town or country, and we provide over £13 million in scholarships each year to graduate students from the UK, EU and overseas.

This programme is eligible for needs-based awards from LSE, including the Graduate Support SchemeMaster's Awards, and Anniversary Scholarships

Selection for any funding opportunity is based on receipt of an application for a place – including all ancillary documents, before the funding deadline. 
Funding deadline for needs-based awards from LSE: 27 April 2020.

In addition to our needs-based awards, LSE also makes available scholarships for students from specific regions of the world and awards for students studying specific subject areas. 

Government tuition fee loans and external funding

A postgraduate loan is available from the UK government for eligible students studying for a first master’s programme, to help with fees and living costs. Some other governments and organisations also offer tuition fee loan schemes.

Find out more about tuition fee loans

Further information

Fees and funding opportunities

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