Retirement is changing dramatically. Where it used to suggest an ending, today it can be a beginning – a time to explore, discover, and get on with the rest of your life. This change has paved the way for Just to be a new type of company. One that sees people as unique individuals, always adapting and evolving, and dares to believe in great things.

If you’d like to become part of that journey then we have a great opportunity to join our diverse Demographic Risk team as a Longevity Risk Actuary, on a permanent basis from our London office.

Reporting to the Head of Longevity Risk the main purpose of the role is to accurately forecast the demographic behaviour of the Group’s insured lives and lives in the Group’s target market, with particular focus on longevity assumptions.

Just is a fast-paced and dynamic company, and we promote an agile way of working. This means that you will be exposed to an exciting breath of both BAU and projects across the team, some of the core areas are:

Guide and support the production of regular demographic risk experience analyses (both internal and external data sources) and report on the key results for management review.
Guide and support the development, calibration and documentation of the longevity risk model as an effective basis for risk quantification and management.
Support the development, regular review and documentation of all demographic risk bases.
Develop and maintain the data, processes and systems used by the Demographic Risk team (DR), including the appropriate quality assurance, controls and documentation.
Oversee the implementation of changes to demographic risk bases.
Skills & experience we’re looking for

Qualified Actuary with relevant levels of experience
Background in longevity would be desirable
Life insurance experience is essential
Ability to plan & deliver projects
Ability and willingness to guide more junior members in the team
Clear understanding of risk management and Solvency II framework
Knowledge of SQL, R and / or Python would be an advantage
Experience of data manipulation and analysis
Experience of systems development and process improvement
Some experience in statistical or mathematical modelling