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Actuarial Manager - Stochastic Modelling

Employer
Oliver James
Location
Homeworking
Salary
Negotiable
Closing date
14 Jun 2022
Reference
JOB-052022-168981

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Sector
Life insurance
Contract Type
Permanent
Hours
Full Time
Experience/Function
Qualified, Nearly qual (11+ exams)

Job Details

  • Our client has multiple UK offices however the successful candidate will be free to work from home as they wish.

Our client is a highly established, global brand with operations worldwide. We're looking to recruit an Actuarial Manager to be part of our clients Stochastic Modelling and Projections team. The Actuarial Manager will support the development, maintenance and operation of stochastic modelling components which underpin key actuarial reporting processes.

Day to day you will oversee ESG production whilst overseeing a team of more junior team members delivering project work. You'll work closely with key senior stakeholders worldwide, assisting with design & development work, predominantly supporting the monitoring, implementation and testing of the IFRS17 projection and forecasting model.

Experience required:

  • Nearly/newly or qualified Actuary
  • Theoretical and practical knowledge of stochastic models and Economic Scenario Generators
  • Knowledge of insurance risk-based capital regimes such as Solvency II or equivalent
  • Managerial experience at a project level e.g. managing several more junior colleagues to deliver a specific task
  • Individuals with an investment or quantitative finance background with suitable qualifications and experience will also be considered.

To be considered please forward your CV to charlotte.walker@oliverjames.com or contact me on 020 3861 9124 for more information.

Company

They have a global team of specialist and established consultants across the UK, Europe and Asia, giving them unparalleled knowledge of their market place. We place on a contract and a permanent basis, in roles ranging from Student Actuary to Chief Actuary.

Company info
Website
Telephone
+44 (0) 207-649-9464

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