Premera Blue Cross

Developing, tuning, and deploying complex AI/ML models within healthcare settings, managing the entire model lifecycle, and collaborating with stakeholders. | Requires 8+ years in data science/engineering, expertise in ML solutions, and experience with advanced interpretability tools, which do not align with your current profile. | Job Description: • Develop and tune generative/agentic AI solutions aimed to solve highly complex problems within the delivery of healthcare or health plan services. • Establish comprehensive tracking of experiments to manage the iterative process of building and testing models ensuring that AI solutions fulfill business requirements. • Provide statistical rigor to these evaluations via the design of controlled tests to measure the impact of changes to the solution. • Form and leverage strong collaborations with AI engineers to scale solutions for production grade performance. • Develop and implement complex agentic workflows that utilize AI agents for autonomous task execution, enhancing operational efficiency and decision-making capabilities. • Solve new business problems by reaching, designing, building, and validating complex or novel machine learning models. • Conduct feature engineering and model optimization. • Manage the complete lifecycle of machine learning models from conception to deployment while following SDLC and responsible AI practices. • Consult with senior and executive level business leaders to scope, model, and recommend AI/ML, technical, or analytic solutions to highly complex problems within healthcare. • Build and ensure consensus with stakeholders regarding the feasibility, tradeoffs, and delivery of recommended solutions. • Research, recommend, and apply causal techniques (RCT, DiD, PSM, causal graph models, counterfactual reasoning, etc.) to estimate treatment effects to quantify or validate business benefit of complex health plan activities. • Explain business impact to program owners and leadership using approaches that are meaningful to those audiences. • Partner with program owner in the promotion or publications of results when applicable. • Participate in code peer reviews and quality assurance testing. • Troubleshoot issues as they arise to solve problems independently and collaboratively. • Serve as the technical subject matter expert to establish best practices for the team and help coach the team via formal and informal initiatives. • Maintain regular contact with customers through development cycle to ensure each step of implementation tracks customer’s needs. • Lead analytics projects applying a working knowledge of Agile and SCRUM project methodologies. Requirements: • Bachelor’s Degree in Statistics, Computer Science, Programming, Data Science, or similar quantitative field. • (5) years of experience in quantitative analytics, programming, and/or data engineering or data science for Level III. • (8) years of experience in quantitative analytics, programming, and/or data engineering or data science for Level IV. • Master’s/PhD Degree in Statistics, Computer Science, Data Science or similar quantitative field (preferred). • 2+ years of experience developing solutions using language and reasoning models (preferred). • Familiarity with agentic frameworks and protocols and knowledge graphs (preferred). • 5+ years of experience in developing and optimizing ML solutions using Python’s core data science scientific stack (NumPy, Pandas, Matplotlib and scikit-learn) (preferred). • Familiarity with advanced model interpretability libraries (e.g., SHAP, LIME) (preferred). • Experience with open-source environments (preferred). • 3+ years of experience with ML lifecycles in production contexts, including metrics definition, drift monitoring and alerting, automated retraining, etc. (preferred). Benefits: • Medical, vision, and dental coverage with low employee premiums. • Voluntary benefit offerings, including pet insurance for paw parents. • Life and disability insurance. • Retirement programs, including a 401K employer match and a pension plan that is vested after 3 years of service. • Wellness incentives with a wide range of mental well-being resources for you and your dependents, including counseling services, stress management programs, and mindfulness programs, just to name a few. • Generous paid time off to reenergize. • Tuition assistance for both undergraduate and graduate degrees. • Employee recognition program to celebrate anniversaries, team accomplishments, and more. • Commuter perks to make your trip to work less impactful on the environment and your wallet. • On-campus model provides flexibility for hybrid employees with access to on-site resources, networking opportunities, and team engagement.