Manager, Actuarial Data, Automation and AI

We are looking for a forward-thinking actuarial manager to help shape the future of reporting, analytics, and AI within our Actuarial function.

The Manager, Actuarial Data, Automation and AI (ADAA) will drive high-impact initiatives that modernize reporting processes, unlock better business insights, and scale practical AI solutions.

Key Responsibilities:

• Lead the implementation of Actuarial initiatives within the Future Finance Program+ (FFP+), transforming actuarial processes through workflow automation, process redesign, enhanced reporting analytics, and the adoption of AI solutions.
• Act as PACS Project Manager to ensure successful delivery of PACS FFP+ initiatives and Actuarial Tech projects, developing detailed project plans, defining scope, timelines, budgets, and resource allocation.
• Assist in defining an actuarial AI roadmap, identifying AI use cases, and coordinating cross-functional delivery of pilot and scaled AI solutions.

Requirements:

• Strong knowledge of actuarial reporting processes and the ability to modernize them through automation and systems change.
• Demonstrated ability to design and implement end-to-end process flows, embedding data validation, governance, and quality standards.
• Experience in actuarial analytics, including translating complex analysis into actionable management insights applying advanced analytical techniques.
• Critical thinking, analytical, and problem-solving skills.
• Leadership and excellent communication skills, capable of explaining technical concepts to non-actuarial stakeholders.
• Self-driven and able to work independently in a fast-paced environment.

Working Experience:

• 6+ years of strong experience in actuarial reporting or business intelligence/data analytics/business analyst role.
• Expertise in project management or consulting in the insurance industry.
• Experience in AI solution implementation to improve efficiency or Data analytics to get actionable insights will be a plus.

Professional Qualifications:

• Qualified or near-qualified actuary, or an experienced actuarial professional with strong business credibility.

Education:

• Degree in Actuarial, Mathematics, Statistics, Business Analytics, Data Science, Computer Science.

Technical Skills:

• Proficiency in statistical models, Python, SQL, and business intelligence tools (e.g., Power BI).
• Technical proficiency such as methodologies like Agile or Scrum.
• Advanced data analytical technique or Machine Learning or AI knowledge are advantageous.