Provide advanced analytics support within the Business Analytics function
Apply data science techniques to solve business problems across various analytical areas
Develop, validate, and maintain high-quality, robust predictive models and AI solutions that meet business requirements
Utilize multiple sources of data along with machine learning techniques to improve model performance
Write clean, modular, and well-documented code for production
Interpret data and model outputs to generate actionable insights and recommendations

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
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.

Data Scientist – Health and Risk Solutions

Key skills