(Senior) Actuarial Analyst, Digital Solutions

Data Discovery and Assessment

• Perform initial assessment of diverse data sources, including data quality, completeness and suitability.
• Conduct exploratory analysis and define data requirements and assumptions.

Validation and Insight Translation

• Validate analytics findings through benchmark analyses, back-testing and sanity checks.
• Quantify impacts, interpret results and communicate implications to technical and non-technical stakeholders.

Risk Implications and Documentation

• Support methodology development, scenario design and projections for risk implication exercises.
• Prepare clear documentation of assumptions, methods and controls for governance and audit.

Implementation and Monitoring

• Define post-implementation monitoring frameworks and KPIs.
• Perform ongoing experience analyses, detect and escalate adverse trends and recommend remedial actions.

Stakeholder Collaboration and Delivery

• Work in cross-functional teams with data scientists, underwriters and business consultants to deliver projects on time.
• Provide analytical support for internal and external ad hoc requests and contribute to client presentations and reports.

Your Profile

• Associate or nearly/newly qualified actuary from a recognised actuarial body (ASA, FSA, FIA, FFA or FIAA).
• 3+ years of experience in life or health insurance or reinsurance.
• Experience with actuarial analytics (e.g., experience studies).
• Familiarity with AI/ML use cases in the insurance industry.
• Proficient in Python and SQL; able to build reproducible, well-documented analyses.
• Experience with actuarial software (e.g., AXIS) will be a strong advantage.
• Demonstrated technical and analytical capability, with logical, structured problem-solving skills and attention to detail.
• Solid understanding of life insurance operations (underwriting, actuarial, risk management and claims).
• Collaborative team player with high ownership, the ability to work independently and adaptability in a dynamic business environment.
• Effective prioritisation skills; comfortable managing timelines and balancing multiple deliverables.
• Willingness to learn in a dynamic environment; proactive and accountable, with a strong sense of ownership.