Director, Data Science

Sun Life U.S. is one of the largest providers of employee and government benefits, helping approximately 50 million Americans access the care and coverage they need. Through employers, industry partners and government programs, Sun Life U.S. offers a portfolio of benefits and services, including dental, vision, disability, absence management, life, supplemental health, medical stop-loss insurance, and healthcare navigation. We have more than 6,400 employees and associates in our partner dental practices and operate nationwide.

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Purpose:

helping our Clients achieve lifetime financial security and live healthier lives. Our values shape how we work: caring, authentic, bold, inspiring, and impactful. When you join Sun Life, you'll work with passionate colleagues and empowering leaders who support your growth and celebrate your contributions, so you can make a meaningful difference in our Clients' lives. Visit our website to learn more.

Job Title:

Director, Data Science October 2026 Band: GCF 7.2 Direct Manager: AVP, Business Analytics

Position Overview:

This role provides advanced analytics leadership for an analytics agile squad within the Business Analytics function. The Director is responsible for advancing how Sun Life US group businesses use machine learning and emerging AI capabilities to improve underwriting, pricing, and related business decision-making. The role will identify, prioritize, and deliver high-value opportunities across new business and renewal underwriting workflows where advanced analytics can improve risk assessment, efficiency, and business outcomes.

Initial areas of support may include product offerings in Employee Benefits, with the opportunity to support other offerings as priorities evolve.

The Director is accountable for the end-to-end delivery, deployment, adoption, and ongoing improvement of advanced analytics solutions supporting the assigned roadmap. This role will build and develop a team of data scientists, establish analytical best practices, and partner closely with business stakeholders, technology, and governance teams to ensure solutions are reliable, explainable, fit for purpose, and supported by appropriate human oversight.

Success will be measured by sustained adoption and measurable improvements in business outcomes.

• Lead advanced analytics solution development for new business and renewal underwriting, pricing, and related decision processes across supported Sun Life US group businesses.
• Shape and maintain a prioritized roadmap of high-value use cases aligned with business strategy, stakeholder needs, measurable outcomes, and emerging analytical opportunities.
• Translate business problems into clear analytics product requirements, success measures, implementation plans, and adoption strategies.
• Evaluate opportunities to improve multi-step business processes through improved information gathering, analysis, recommendations, and workflow coordination while maintaining appropriate human judgment and oversight.
• Partner with Underwriting, Actuarial, Product, Distribution, Finance, Technology, and other stakeholders to deliver solutions that are workflow-ready, scalable, secure, and compliant.
• Apply expertise in data science, machine learning, AI, validation, and quality controls to ensure solutions are accurate, reliable, explainable, and fit for business use.
• Drive solution adoption by partnering with business leaders and SMEs on training, feedback capture, change management, and measurement of productivity, decision quality, and business value.
• Manage and develop a team of data scientists, balancing team development, delivery priorities, and long-term capability building.
• Monitor solution performance, user feedback, data quality, model behavior, and business outcomes to identify enhancements and ensure sustained value after deployment.
• Communicate technical concepts, risks, recommendations, and business impact clearly to technical and non-technical audiences, including senior stakeholders.

• Demonstrated expertise with a broad range of programming languages, applications and data environments (e.g., Python, SQL, Snowflake, Dataiku)
• Demonstrated expertise in data science including conditioning, modeling, integration, visualization, deployment support, and ongoing monitoring
• Strong knowledge of the statistical, machine learning, and analytical foundations of data science.
• Experience leading analytical…