Vice President and Head of Data Management
Summary
Leads data management and actuarial modeling for life reinsurance, building stochastic models, maintaining data warehouses, and supervising analysts using SQL, Excel, and actuarial software.
Analysing and reporting of risk components through development and maintenance of stochastic simulation models
Supporting other aspects of the life reinsurance business, including financial modelling, pricing, experience studies, and performing sensitivity testing
Supervising and mentor analysts that report directly to this position
Responsibility for the development and maintenance of data warehouse to store and administer variable annuity policyholder data, and the development and production of standard and ad hoc data reports
Development and maintenance of experience studies including lapse and annuitisation
Supervising the development of a claim verification protocol for variable annuities
Reviewing and approving traditional life reinsurance claims
Maintaining all software/systems specific to Chubb Tempest Life Re (SQL/data warehouse, Risk Agility FM, Moody’s Analytics ESG, TAI for traditional life block) and act as CTLR connection with corporate IT
Undergraduate or graduate degree in Mathematics, Finance, Economics or Actuarial Science
A minimum of seven years’ experience building actuarial models for U.S. life (re)insurance products, including models for liability projections, experience and persistency analysis, claims analysis, policy data administration, and financial/accounting data maintenance
Strong expertise (minimum seven years’ experience) in information technology
Must include experience with actuarial projection software, SQL programming, Excel, Access and database warehousing. Knowledge of Risk Agility FM, Moody’s Analytics ESG, and/or worker/manager structures highly desirable
Capital markets knowledge and/or experience (at least one year)-familiarity with Bloomberg, CFA designation a plus
Familiarity with stochastic modelling and economic scenario generators, via work experience or education
Genuine aptitude for working in a small team environment; and
Ability to meet tight deadlines
Successful applicant will be able to work extended hours and weekends when required