Are you considering a career as a professional statistician in industry? This course will provide you with the necessary advanced knowledge and skills. This masters course differs from the Statistics MSc, by providing specialised training in probability models, particularly suited for roles in business and finance.
Well qualified statisticians and those skilled in using probability models are in demand world-wide as the amount of digital data we generate increases. Employment opportunities are broad in sectors such as:
You'll study three compulsory modules covering the fundamentals of statistics and stochastic models. This will provide the basis for the remaining optional modules. These include options such as Mathematical Finance and Statistical Machine Learning.
You will learn to develop, implement, and test advanced statistical techniques, learn how to interpret large and complex data, and to extract relevant insights from it. The masters will enable you to develop computing skills in using R too. The course can lead to careers in data science, healthcare and the digital economy.
In the summer you'll complete a dissertation. This will be in collaboration with staff from the school's internationally recognised Statistics and Probability Section, or one of our industry partners, such as Capital One.
The course is split between core and optional modules.
You will study the compulsory modules in Statistical Foundations, Classical and Bayesian Inference and Stochastic Models. This will provide you with the knowledge and skills required to complete your chosen optional modules during the rest of the year.
On completion of your optional modules, you will complete a written research dissertation. You will receive one-to-one support from your supervisor who will offer advice and guidance during your dissertation.
During the year you will study a total of 180 credits. 120 credits worth of taught modules and the 60-credit dissertation.
How you will learn
Some modules will be taught alongside students from other courses.
How you will be assessed
You will be awarded the Master of Science Degree provided you have successfully completed the taught stage by achieving a weighted average mark of at least 50% with no more than 40 credits below 50% and no more than 20 credits below 40%.
You must achieve a mark of at least 50% in the dissertation.
Contact time and study hours
The number of formal contact hours varies depending on the optional modules you are studying. As a guide, in the Autumn and Spring semesters you will typically spend around 14 hours per week in lectures.
You will work on your research project between June and September, usually based at the University.
Teaching is provided by academic staff within the School of Mathematical Sciences. All modules are typically delivered by Professors, Associate and Assistant Professors. Additional support in small group and practical classes may involve PhD students and post-doctoral researchers.
The majority of your lecturers and tutors will be based within the mathematics building. This means if you need to get in touch with them during office hours, they can be contacted easily as they are close by.
We offer individual careers support for all postgraduate students.
Expert staff can help you research career options and job vacancies, build your CV or résumé, develop your interview skills and meet employers.
More than 1,500 employers advertise graduate jobs and internships through our online vacancy service. We host regular careers fairs, including specialist fairs for different sectors.
Alongside their statistical knowledge and skills in probability, our graduates leave Nottingham with valuable skills in:
Statisticians are required to work in many sectors including banking, education, finance, healthcare, sport and transport.
Previous graduates work as:
97.5% of postgraduates from the School of Mathematical Sciences secured graduate level employment or further study within 15 months of graduation. The average annual salary for these graduates was £28,131.*
* HESA Graduate Outcomes 2020. The Graduate Outcomes % is derived using The Guardian University Guide methodology. The average annual salary is based on graduates working full-time within the UK.
Collaboration with Nottingham-based Capital One who we have worked with to set previous research project titles.
Representatives from industry, some of whom are Nottingham graduates, also provide guest lectures throughout the year.
Imperial College London
September 01, 2022
King’s College London
King's College Hospital, Denmark Hill, London, UK
October 01, 2022
Lancaster University, Bailrigg, Lancaster, UK
October 01, 2022