Actuary - Research, Analytics and Data
07 December 2018
Web Ref : 438
Job Description: • Internal and external research relating to pricing, products, underwriting, claims and other areas related to life insurance • Understanding data and applying modern analytical techniques to the data • Implementing practical changes based on research and analytics in various areas of business • Support of analysis and assessment of life and health reinsurance portfolios for the purposes of risk management, experience study, planning and quotation • Supporting large research projects and surveys • Presentations and training measures for clients • Marketing activities, including giving presentations at conferences and writing articles • Participation in international projects Experience/Qualifications: • Applicants should have graduated with degrees in Actuarial Science or Mathematics and be part-qualified with successful exam progression or recently qualified actuaries • Applicants with Master’s level qualification in statistics, mathematics or computer sciences and relevant experience will also be considered • Applicants should also have: significant experience in applying statistical and machine learning techniques in financial services or related business to solve problems in practical and implementable way • Experience with researching and assessing the business relevant impact of external trends is also very important Requirements: • Excellent skills in actuarial modelling, data and statistical analysis • Excellent online research skills • Good commercial awareness • Excellent numerical and analytical skills • Excellent IT skills (MS Office, SQL Server, Working with large datasets) • Strong statistical software skills (R including machine learning, GLMs) • Strong interpersonal skills with an ability to work effectively as part of a team, deal with people at all levels and in all areas of the business and engage with clients • Strong communication skills including verbal and written skills including the ability to summarize and explain complex information clearly and concisely
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