AI/Data Scientist

Join Our Team: Do Meaningful Work and Improve People’s Lives

Our purpose at Premera Blue Cross, to improve customers’ lives by making healthcare work better, is far from ordinary. As an AI/Data Scientist, you'll have the opportunity to drive real change by transforming healthcare. Premera is committed to being a workplace where people feel empowered to grow, innovate, and lead with purpose, fostering a culture of collaboration and continuous development. This commitment has earned us recognition as one of the best companies to work for. Learn more about how Premera supports our members, customers and communities through our Healthsource blog: https://healthsource.premera.com/.

As an AI/Data Scientist, you will apply advanced AI, machine learning, and analytical skills to design, develop, and deploy AI solutions with measurable impact on the most challenging problems within healthcare. You will understand business challenges, research and conceptualize AI-enabled solutions, and work collaboratively to bring them to life, measuring and conveying business value to stakeholders. This is a telecommuter position, working from home.

What you'll do:

• Develop and tune generative/agentic AI solutions to solve highly complex problems within healthcare delivery or health plan services.
• Establish comprehensive tracking of experiments to manage the iterative process of building and testing models, ensuring AI solutions fulfill business requirements.
• Provide statistical rigor to evaluations via controlled tests to measure the impact of solution changes.
• Form strong collaborations with AI engineers to scale solutions for production grade performance.
• Develop and implement complex agentic workflows utilizing AI agents for autonomous task execution, enhancing operational efficiency and decision-making.
• Solve new business problems by researching, 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, 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 healthcare problems.
• Build consensus with stakeholders regarding the feasibility, tradeoffs, and delivery of recommended solutions.
• Research, recommend, and apply causal techniques (e.g., RCT, DiD, PSM, causal graph models, counterfactual reasoning) to estimate treatment effects and quantify business benefit.
• Explain business impact to program owners and leadership using meaningful approaches.
• Participate in code peer reviews and quality assurance testing, troubleshooting issues independently and collaboratively.
• Serve as the technical subject matter expert, establishing best practices for the team and coaching via formal and informal initiatives.
• Maintain regular contact with customers through the development cycle to ensure implementation tracks needs.
• Lead analytics projects applying working knowledge of Agile and SCRUM methodologies.

What you'll bring:

Required Qualifications

• Bachelor’s Degree in Statistics, Computer Science, Programming, Data Science, or similar quantitative field.
• Eight (8) years of experience in quantitative analytics, programming, and/or data engineering or data science.

Preferred Qualifications

• Master’s/PhD Degree in Statistics, Computer Science, Data Science or similar quantitative field.
• Two (2) years of experience developing solutions using language and reasoning models.
• Familiarity with agentic frameworks and protocols and knowledge graphs.
• Five (5) years of experience in developing and optimizing ML solutions using Python’s core data science scientific stack (NumPy, Pandas, Matplotlib and scikit-learn).
• Familiarity with advanced model interpretability libraries (e.g., SHAP, LIME).
• Experience with open-source environments.
• Three (3) years of experience with ML lifecycles in production contexts, including metrics definition, drift monitoring, alerting, and automated retraining.
• Strong track record of using quantitative approaches, including statistics and machine learning, to solve analytical problems.

Knowledge, Skills, And Abilities

• Deep expertise in one or more of the following areas with working knowledge and interest in others.
• Familiarity with best practices in code quality, version control, and system architecture.
• Experience working with open-source frameworks such as Transformers, Langchain/Langraph or similar, REST API’s, and optimization using asynchronous frameworks.
• Advanced in SQL for feature engineering, with an ability to handle structured and unstructured data in various research contexts.
• Comfortable working with evolving data formats and tools, leveraging data management best practices to support experimentation and prototyping.
• Skilled in a wide variety of statistical analyses (e.g., hypothesis testing, experimental design, A/B testing, regression analysis, clustering, time series analysis, anomaly detection and sequence analysis) using best practices tools such as Statsmodels, PyMC, Darts, Prophet etc. to champion data-driven decision making.
• Experienced at establishing experiment tracking to manage the iterative process of developing AI solutions.
• Familiar with measuring and monitoring traditional telemetry and gen AI observability metrics to ensure the behavior and outputs of AI solutions in production.
• Proficient at ethical AI practices including explainable AI, fairness, and mitigation of bias/hallucinations.
• Familiarity with distributed computing and/or distributed databases (Hadoop, NoSQL, etc.).
• Demonstrated experience in data extraction, manipulation, data management, predictive and descriptive data modeling, forecasting, trending, interpreting, displaying, and communicating results/recommendations.
• Fluency with data visualization tools such as Matplotlib, Seaborn, Bokeh, Plotly, etc., for data exploration and presentation.
• Strong written communication skills and ability to communicate complex quantitative analysis in a clear, precise, and actionable manner.
• Strong interpersonal skills with the ability to work both independently and as a member of a team.
• Strong knowledge of mathematics, statistics, and probability.
• Able to combine pieces of information to form general rules or conclusions as well as find relationships among seemingly unrelated business or healthcare events.
• Able to anticipate business customer’s analytics needs and proactively conceptualize and champion high-value data product solutions.

Premera Total Rewards

Our comprehensive total rewards package provides support, resources, and opportunities to help employees thrive and grow. We offer a broad array of rewards including physical, financial, emotional, and community benefits, such as medical, vision, and dental coverage, voluntary benefits (e.g., pet insurance), life and disability insurance, and retirement programs (401K employer match and pension plan vested after 3 years). Wellness incentives, mental well-being resources, generous paid time off, and tuition assistance for continuing education are also provided. We celebrate employee recognition for anniversaries and team accomplishments.

Key skills/competency

• Advanced AI/ML Solutions
• Generative AI Development
• Statistical Modeling & Analysis
• Data Engineering & SQL
• Machine Learning Lifecycle (MLOps)
• Causal Inference Techniques
• Python Data Science Stack
• Agentic AI Workflows
• Ethical AI Practices
• Data Visualization