Data Science Library

Data Analytics Library


Actuaries are well placed to add a lot of value as a Data Scientist due to their strong quantitative background coupled with business insight. The purpose of the Data Science Library is to provide practical tools and resources for actuaries wishing to develop their data analytics skills - either as part of their current actuarial work or by moving into a data science role.

The Library may also be a useful guide for other professionals who work, or have an interest in, data science.

Data science is amongst the leading trends in the insurance industry as identified by top insurance and technology consulting firms  (for example Top issues in Insurance (PwC US, 2016), Top 10 Trends in Life Insurance (Cap Gemini) and Top 10 Trends in P&C Insurance (Cap Gemini, 2018)).  Recent applications include telematics for car insurance, sales predictions and fraud detection.

The Library is not meant to be a comprehensive repository in this fast-developing field. However if you have any feedback on the library or any questions about data acience and actuaries, please Contact the Society.

Structure of the Data Science Library

The Data Science Library is a live document to be maintained on an ongoing basis as materials and experience evolves in this new discipline.

The library has the following structure:

  1. Introduction – purpose of the library and contact details;
  2. Support from the Society  - description of the support provided by the Society of Actuaries in Ireland (the “Society”) including special membership for wider fields members;
  3. Getting Started – if you are interested in starting data science , this page links to:
    • Step by step guide - steps to get started in data science ;
    • Courses and skills - list of university and other online courses and required skillset for those keen on becoming a data scientist;
  4. Materials - reference materials (articles and books), tutorials, tools and other resources;
  5. Events and opportunities - links to current and past talks held by the Society as well as links to data science opportunities including competitions, study groups and more.

Where this information includes links to other sites and resources provided by third parties, these links are provided for general information only. The Society assumes no responsibility for the contents of such third party offerings.