Data Scientist–Health and Risk Solutions

Data Scientist–Health and Risk Solutions

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.

Sun Life embraces a hybrid work model that balances in‑office collaboration with the flexibility of virtual work. Internal candidates are not required to relocate near an office.

The Data Scientist provides advanced analytics support within the Business Analytics function that applies the power of data with machine learning to improve business outcomes across the Health and Risk Solutions business. This team is expected to work closely with other teams across the organization, including functional teams and the analytic agile squads supporting AI use cases within various business domains.

This position reports to the Director of Advanced Analytics Transformation within the Health and Risk Solutions business. Responsibilities include helping to develop and monitor predictive model and AI solutions to support our pricing, underwriting and clinical review processes, as assigned. Additional responsibilities may include applying machine learning techniques to streamline and automate aspects of these processes and promoting a culture of data‑driven risk‑based decisions.

• Apply data science techniques to solve business problems across various analytical areas, including exploratory data analysis, feature engineering, predictive modeling, and visualization.
• Develop, validate, and maintain high‑quality, robust predictive models and AI solutions that meet business and technical requirements.
• Utilize multiple sources of data, including structured and unstructured data, along with a variety of machine learning techniques to improve model performance and interpretability.
• Write clean, modular, and well‑documented code that can be deployed and maintained in production.
• Interpret data and model outputs to generate clear actionable insights and recommendations that drive business decisions.

• Ability to work with a diverse range of people.
• BS/MS in a statistical, mathematical, or technical field (e.g., computer science, actuarial science).
• 2+ years of experience in developing and implementing data science techniques.
• Healthcare or health insurance experience preferred, particularly with experience in pricing, underwriting and clinical domains. Will consider candidates that have experience in other insurance product lines.
• Demonstrated academic or industry experience with generative AI including prompt engineering, RAG workflows and integrating LLMs into business process.
• Familiarity with MLOps practices, including model deployment, monitoring, and lifecycle management.
• Strong knowledge of statistical and data science techniques, including machine learning, data visualization, A/B testing, and experience with databases.
• Proficiency in Python and SQL for data manipulation, modeling, and automation.
• Experience with machine learning framework and libraries.
• Ability to turn proof‑of‑concept model into production‑ready code and reproducible workflows.
• Commitment to data compliance, model governance and security protocols.
• Strong business acumen to understand why and how the work we do will impact our business stakeholders.
• Strong problem‑solving skills and effective communication, with an ability to explain technical concepts to a non‑technical audience.

$84,900-$127,400

We are committed to fostering an inclusive environment where all employees feel they belong, are supported and empowered to thrive. We encourage applications from qualified individuals from all backgrounds.

We will make reasonable accommodations to the known physical or mental limitations of…