Senior Actuarial Analyst - Data & AI Analytics Lead

Munich Reinsurance

Singapore

On-site

SGD 110,000 - 160,000

Full time

2 days ago
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Job summary

Munich Reinsurance in Singapore seeks a (Senior) Actuarial Analyst to bring actuarial expertise across digital analytics projects from discovery to monitoring. You will work with data scientists, underwriters and client stakeholders to ensure actuarial rigour and robust risk management.

The role covers data discovery, validation, risk implications, implementation and monitoring, with cross-functional teamwork and clear communication as essential.

Qualifications

  • Associate or near-qualified actuary from a recognised actuarial body.
  • 3+ years of experience in life or health insurance or reinsurance.
  • Experience with actuarial analytics (e.g., experience studies).
  • Proficient in Python and SQL with reproducible analyses.
  • Familiarity with AI/ML use cases in the insurance industry.

Responsibilities

  • Perform data source assessment, data quality, completeness and suitability.
  • Conduct exploratory analysis and define data requirements and assumptions.
  • Validate analytics findings with benchmark analyses and back-testing.
  • Quantify impacts, interpret results and communicate implications to stakeholders.
  • Define post-implementation monitoring frameworks and KPIs.
  • Work in cross-functional teams with data scientists, underwriters and consultants to deliver projects on time.

Skills

Python
SQL
AXIS
Actuarial analytics

Education

Actuarial qualification (ASA/FSA/FIA/FFA/FIAA)

Tools

AXIS

Job description

Munich Reinsurance in Singapore seeks a (Senior) Actuarial Analyst to bring actuarial expertise across digital analytics projects from discovery to monitoring. You will work with data scientists, underwriters and client stakeholders to ensure actuarial rigour and robust risk management.

The role covers data discovery, validation, risk implications, implementation and monitoring, with cross-functional teamwork and clear communication as essential.

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