provide advanced analytics support within the Business Analytics function
apply the power of data with machine learning to improve business outcomes across the Health and Risk Solutions business
work closely with other teams across the organization, including functional teams and the analytic agile squads supporting AI use cases within various business domains
report to the Director of Advanced Analytics Transformation within the Health and Risk Solutions business
develop and monitor predictive model and AI solutions to support pricing, underwriting and clinical review processes
apply machine learning techniques to streamline and automate aspects of processes
promote a culture of data-driven risk-based decisions
interpret data and model outputs to generate clear actionable insights and recommendations that drives business decisions

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
demonstrated academic or industry experience with generative AI including prompt engineering, RAG workflows and integrating LLMs into business process is required
healthcare or health insurance experience preferred
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
strong problem-solving skills and effective communication, with an ability to explain technical concepts to a non-technical audience

Data Scientist – Health and Risk Solutions

Key skills