University of Leicester

What you'll study

This master's integrates traditional actuarial topics with practical data-analytics techniques. You will study the mathematical and statistical foundations of actuarial work alongside modules that teach programming, machine learning and applied data handling.

• Core actuarial modules: mathematical life contingencies, survival models, stochastic modelling and financial mathematics that underpin pricing, reserving and valuation of insurance and pension liabilities.
• Probability and statistical modelling: advanced probability theory, regression and generalized linear models, time series and survival analysis as applied to risk and insurance data.
• Data analytics and computing: programming for data analysis (typically Python/R), database handling, machine learning methods, and practical data visualisation for actuarial problems.
• Risk and finance: topics in credit and market risk, investment modelling, and enterprise risk management techniques used by insurers and financial firms.
• Project or dissertation: an applied research project or dissertation working on a substantive actuarial or data-analytics problem, often using real or simulated industry datasets.
• Optional/specialist modules: depending on availability, you may choose modules in areas such as pensions, health economics, reinsurance, or advanced simulation techniques.

The programme places emphasis on problem-solving: combining theory with practical exercises, case studies and computing labs. It is structured to prepare students for the technical demands of actuarial work while equipping them with data-science tools increasingly used across the sector.

Entry requirements

Applicants are normally expected to have a good UK honours degree (2:1 or equivalent) in mathematics, statistics, actuarial science, economics with strong quantitative content, engineering or another closely related discipline with substantial mathematical training. Candidates with a 2:2 may be considered if they can demonstrate relevant professional or quantitative experience.

• Mathematical background: competence in calculus, probability and linear algebra is expected. Prior exposure to statistics and basic programming is advantageous.
• International applicants: equivalent qualifications from recognised institutions are acceptable; English language proficiency is required where the first language is not English (e.g. IELTS/TOEFL or other approved tests at the University of Leicester's standard level).
• Professional experience: relevant work experience or exemptions from professional actuarial exams may strengthen an application but are not usually required for entry.

Career prospects

Graduates from this programme are well placed for roles that combine quantitative analysis with business decision-making. Typical career destinations include:

• Actuarial analyst positions in life, general insurance and reinsurance firms
• Risk analyst or risk modelling roles in financial services and consulting
• Data scientist, data analyst or quantitative analyst roles in insurance, fintech and wider financial sectors
• Pensions analyst and employee benefits consultancies
• Further professional training — many graduates progress to take professional actuarial exams (such as those of the Institute and Faculty of Actuaries) while working or studying for exemptions where applicable.

The mix of actuarial theory and data analytics increases employability across traditional actuarial pathways and data-driven roles, including positions that demand programming and machine-learning capability.

Why study at University of Leicester

The University of Leicester has an established tradition in mathematical and statistical teaching and research, offering students access to experienced academic staff working on applied risk, actuarial science and data analytics topics. The programme benefits from applied coursework, computing labs and opportunities to work on industry-relevant projects.

• Applied, research-informed teaching: modules are taught by academics with expertise in actuarial science, statistics and data science, ensuring coverage of both theoretical foundations and practical techniques.
• Industry links and employability: the department maintains contacts with actuarial employers and professional bodies, supporting placement opportunities, guest lectures and careers guidance tailored to actuarial and data careers.
• Facilities: students have access to computing resources, statistical software and dedicated support for quantitative MSc projects.
• Location and community: Leicester offers a supportive student environment with good transport connections to major UK financial and insurance centres, making it a practical base for internships and networking.

Overall, the MSc Actuarial Science with Data Analytics at the University of Leicester is aimed at mathematically strong students who want a rigorous actuarial education enhanced with modern data-analytics skills to meet employer demand in insurance, pensions and financial services.