Catastrophe Risk Modeller

Job title: Catastrophe Risk Modeller
Location: London
Industry: Insurance
Salary: £45,000
Reference: 1473
Contact name: Toni Dines
Contact email: Toni@teamboxtree.co.uk

Job description

Boxtree have been appointed by a global reinsurance brokerage who are looking to appoint a catastrophe risk modeller to join the organisation and work closely with brokers and clients alike.

 

Preferably with experience within RMS and AIR, you will be involved in all lines of business throughout the brokerage and will have already benefited from years of experience utilising modelling tools to conduct technical risk modelling.

 

Responsibilities:

  • Working innovatively within the reinsurance analytics team supporting internal brokers and external clients
  • Ensuring accurate and diligent import of data gathered to analyse and assess within modelling software (ideally using RMS Risk Intelligence software or using AIR worldwide.
  • Assisting the profitability and growth throughout the business by identifying unprofitable areas of the business as well as monitoring key catastrophe indicators and identifying with management

 

Required:

  • Experience of catastrophe modelling including strong communication skills with external and internal clients, brokers and analytical teams
  • Previous experience working within an insurance or reinsurance company
  • Confident using Excel and formula calculations
  • Strong mathematical skills to assist with actuarial and loss forecasting analysis

 

Company Benefits:

  • Discretionary bonus based on objective performance
  • Health plan including vision, dental and well-being and critical illness coverage
  • Group income protection and life protection
  • Fantastic holiday structure
  • Many, many more benefits!

 

Please note that we expect a high response to this position if you have not had a response within the next 3 days please assume that on this occasion you have been unsuccessful.

 

Boxtree are very serious about how we regulate and control personal data of our candidates. Please note that by applying for this vacancy you provide Boxtree with your explicit consent to process your personal information which we will re-qualify by contacting you. A copy of our privacy policy outlining how we use and store your personal data is available to view on our website. You can request to be ‘forgotten’ by emailing Lacee Watts please see email via our website).

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