Senior Manager, Artificial Intelligence

The Senior Manager, Artificial Intelligence is a technical leader responsible for designing, developing, and implementing advanced AI and machine learning solutions to address strategic business challenges.

This role is hands-on and project-focused, with direct accountability for delivering high-impact analytics initiatives from conception through to deployment and operationalization.

Responsibilities:

• Partner with business stakeholders to identify opportunities where data science and AI can drive measurable business impact.
• Translate business challenges into analytical problems, defining success metrics and solution approaches.
• Lead end-to-end delivery of analytics use cases from problem framing through deployment and integration.
• Serve as a bridge between business and technical teams ensuring solutions meet business needs.
• Deliver insights and recommendations in a clear, business-friendly manner.
• Drive adoption of analytics solutions by embedding them into workflows and decision processes.
• Quantify and communicate business impact including revenue growth, cost efficiency, claims reduction, and persistency improvement.
• Apply data science techniques to underwriting, claims, customer retention, distribution effectiveness, and personalization.
• Leverage Generative AI and LLMs to enhance business productivity.
• Ensure compliance with regulatory requirements, model governance, and responsible AI standards.
• Collaborate with actuarial, risk, compliance, and IT teams.
• Mentor junior team members and promote data-driven culture.

Required Qualifications:

• Bachelor’s or Master’s degree in a quantitative field such as Statistics, Mathematics, Computer Science, Engineering, or Actuarial Science.
• 6–10 years of experience in data science, AI, or advanced analytics with strong business-facing exposure.
• Prior experience in life insurance or related financial services industries preferred.
• Solid understanding of the life insurance value chain.
• Proven ability to translate business needs into analytical solutions.
• Hands-on experience with machine learning and statistical modeling.
• Proficiency in Python, R, or similar tools.
• Experience working with large and complex datasets.
• Exposure to Generative AI / LLM use cases is highly valued.
• Strong business acumen linking analytics to financial outcomes.
• Experience in agile environments.
• Excellent communication and stakeholder management skills.
• Familiarity with insurance regulations and model governance is an advantage.

Benefits:

• Empowered to learn and grow in a flexible environment.
• Recognition and support for well-being and inclusion.
• Opportunities to shape the future of the organization.