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Capgemini

14134006 - Life Sg Actuarial Analyst

Posted on Nov. 19, 2024

  • Full Time

14134006 - Life Sg Actuarial Analyst

Technical Responsibilities

  • Conversion of existing Python scripts (in AWS) specific to Life and Health Actuarial teams to Google Big Query SQL
  • Testing of the rewritten Big Query SQL logic and sign-off, upon alignment with Actuarial teams
  • Document the requirement, ETL logic, testing plan and test results
  • Business Responsibilities
  • Work closely with finance and actuarial team enterprise architecture team, application development team to understand the applications workflow and requirement, integration pattern with finance cloud platform
  • Conduct business analysis by eliciting, interpreting and analyzing the requirements from actuarial teams and producing specification of actuarial metrics & analysis
  • Act as main liaison between business/actuarial teams and technical delivery team to drive realization of actuarial processes into proper execution, change management and BAU activities
  • Create and maintain accurate and up to date documentations
  • Support the migration of pricing tools in terms of technical accuracy and efficiency
  • Support the actuarial control cycle through assisting the valuation team in the reserving exercise and strategic planning exercise
  • Provide monitoring updates on profitability trends to senior stakeholders. This includes inflation studies, actual vs expected studies for all products, understanding the key profitability/loss drivers and providing recommendations.

Skills Requirement

Must have high technical proficiency with Python and Google Big Query SQL skills
  • Present actuarial recommendations and reports to senior management, effectively translate complex actuarial codes in a clear and concise manner
  • Highly experienced within Life or Health Insurance domain, preferably within 2-3 years’ experience
  • Business Intelligence/Data Warehousing/ETL experience
  • Excellent analytical skills, with the ability to analyze complex data sets and derive actionable insights.
  • Detail-oriented mindset, focusing on accuracy and precision in actuarial calculations and analyses.

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