赫瑞瓦特大學

Overview

Data science today is becoming increasingly important within the actuarial field, and Heriot-Watt has developed this unique new programme to meet this growing actuarial demand.

Actuarial data science combines advanced statistical modelling and analysis with modern computational techniques in order to analyse potentially large datasets arising in insurance and finance. These analyses have the ability to improve forecasts and enhance decision making in an uncertain environment where rapid advancements in technology and data availability are transforming fields of actuarial work. Additionally, they are building synergies with new sectors such as medical and healthcare. This is an area of science and technology that is attracting significant interest and that will continue to grow for the foreseeable future, as more and more industries adopt data-driven and data-centric approaches.

This programme will provide students with intensive and high-quality education in a postgraduate context in the main areas of data science related to actuarial applications, including machine-learning techniques, supervised and unsupervised learning, clustering methods, feature extraction, generalised linear and Bayesian models, ensemble methods, and practical experience of applying these to actuarial data modelling problems.

Students graduating from the MSc will have excellent employment prospects that are not restricted to any one narrow sector of financial services. By their choice of IFoA subjects, they may target the life, pensions, asset management, investment and risk management sectors. They will be in demand in quantitative risk management roles in both banks and insurance companies, as well as fund management companies, hedge funds, consultancies, software vendors and regulatory authorities. The market for graduates with actuarial qualifications complemented with data science skills is growing fast and we expect that it will continue to grow for the foreseeable future. Students will also achieve PgCert and PgDip awards during this course.