The JobServe as a full-stack data and analytics engineer within a business-aligned scrum team. This role designs, develops, and delivers end-to-end solutions-including data pipelines, models, semantic layers,
and visualizations-while playing a hands-on role in enabling AI/ML use cases. In this role you will ensure that data is analytics and AI-ready, support data and feature engineering, and collaborate closely with report developers, data scientists, and AI engineers to bring predictive and prescriptive analytics, as well as generative AI solutions, into production. Deep familiarity with healthcare data and Medicare Advantage business processes is essential.
You Will- Collaborate with business stakeholders across the health plan to translate business needs into actionable analytic, BI, and AI-enabled solutions that deliver measurable value
- Build and refine analytics-ready data sets needed for dashboards, models, and GenAI applications
- Perform hands-on feature engineering and create ML-ready datasets to accelerate model development across health plan priorities such as member experience, operational efficiency, and/or clinical excellence
- Implement and support AI/ML workflows such as RAG, NLP pipelines, Cortex functions, embeddings, and predictive models
- Guide development of, and help maintain, semantic layers and governed metric definitions used across BI dashboards, operational reporting, and AI/ML pipelines
- Build business-facing dashboards and lightweight data-as-a-service applications (Power BI, Streamlit, or similar) that embed predictive, prescriptive, or generative insights for decision-makers
- Collaborate with data scientists and AI engineers to operationalize models-ensuring datasets, features, and inference pipelines are versioned, monitored, and production-ready
- Apply responsible data practices by embedding lineage, quality checks, PHI/PII protection, and responsible AI guardrails directly into your workflows
- Identify and resolve data quality issues that impact business outcomes and proactively recommend data improvements to accelerate delivery of use cases
- Continuously explore new AI/ML capabilities, particularly LLM- or agentic- driven workflows, and integrate them into business-facing solutions where appropriate
- We seek Rebels who are curious about AI and its power to transform how we operate and serve our members.
- Actively support the achievement of SCAN's Vision and Goals.
- Other duties as assigned.
Your Qualifications- Bachelor's degree in Computer Science, Data Analytics, or related field (or equivalent experience).
- Hands-on experience delivering BI and reporting solutions (Power BI, Tableau, or similar) that translate data and AI-driven insights into actionable business decisions
- 3-6 years in data engineering, analytics engineering, or applied ML/AI, ideally in a business-aligned role delivering end-user solutions
- Experience building semantic models and defining governed metrics
- Strong SQL and experience with cloud analytics platforms such as Snowflake, Databricks, or similar.
- Hands-on experience with ETL/ELT tools (Azure Data Factory, Coalesce, dbt, or similar).
- Strong familiarity with Medicare Advantage domains (e.g., claims, enrollment, provider data, risk adjustment, Stars/quality, etc.)
- Experience building ML-ready datasets and supporting data scientists in training and inference workflows.
- Familiarity with LLM/NLP use cases (RAG, embeddings, vector stores)
- Proficiency in Python for data engineering and light ML workflows (Pandas, PySpark, scikit-learn, or similar).
- Experience working in agile delivery frameworks (Scrum/SAFe) with rapid iteration in business-facing teams. Familiarity with agile delivery methods (Scrum/SAFe) and software (e.g. Azure DevOps, JIRA, etc).
- Healthcare & Medicare Advantage expertise: Understands health plan data domains (claims, provider, member, risk adjustment, quality) and how analytics/AI/ML can improve outcomes
- AI/ML Enablement: Comfortable working side-by-side with data scientists and ML engineers to ensure models are production-ready, performant, and aligned to healthcare business needs
- Full-stack mindset: Ability to span the data lifecycle-back-end pipelines, semantic models, and front-end dashboards-integrating AI insights along the way
- Business acumen: Connects technical work to strategic health plan objectives, such as Stars improvement, member engagement, and cost management
- Problem solving: Resourceful in handling structured and unstructured healthcare data, able to design innovative solutions for AI/ML pipelines
- Clear communicator: Can explain technical concepts to non-technical users and partner across business and technology groups
- Mentorship: Serves as a mentor to help elevate BI/analytics colleagues in best practices for data engineering and AI enablement as well as delivering business value via data and analytics
- Adaptability: Learns emerging AI/ML tools and healthcare regulations quickly and applies them responsibly in production environments
We're always looking for talented people to join our team! Qualified applicants are encouraged to apply now!
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