Analytics, Full-Stack Engineer

SCAN Health Insurance

29d

About The Position

The Job Serve 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.

Requirements

Required to work PST time zone.
Bachelor’s degree in Computer Science, Data Analytics, or related field (or equivalent experience).
3–6 years of experience in data engineering, analytics engineering, or applied ML/AI.
Strong SQL skills and practical experience with modern cloud data platforms (Snowflake, Databricks, or similar).
Hands-on experience with ETL/ELT tools (Azure Data Factory, Coalesce, dbt, or similar).
Experience in healthcare data, particularly within Medicare Advantage health plans—claims, enrollment, provider, risk adjustment, and quality (HEDIS/Star ratings).
Experience supporting AI/ML workflows—feature engineering, ML-ready datasets, and/or deploying models into production.
Strong familiarity with LLM or NLP use cases (RAG, embeddings, vector databases); experience with transformer models such as BERT preferred.
Proficiency in Python for data and ML engineering (Pandas, PySpark, scikit-learn, or similar).
Familiarity with agile delivery methodologies (Scrum/SAFe).
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.
Collaboration & communication: Works seamlessly with business, analytics, and AI/ML colleagues; explains technical work to diverse stakeholders
Adaptability: Learns emerging AI/ML tools and healthcare regulations quickly and applies them responsibly in production environments.

Responsibilities

Collaborate with business stakeholders across the health plan to translate business needs into actionable technical and AI/ML-enabled solutions.
Design, build, and maintain production-grade data pipelines using Azure Data Factory, Coalesce, Snowflake, and SQL to prepare data for analytics and ML workloads.
Engineer features and ML-ready datasets to support data scientists and AI engineers in model training, validation, and deployment for use cases like risk stratification, care management, and provider performance.
Model Training and Optimization: Train AI models and optimize their performance to ensure they meet business requirements.
Contribute to the design and implementation of AI/ML workflows, including Retrieval-Augmented Generation (RAG), NLP pipelines, Snowflake Cortex, and predictive models that improve plan operations and member experience.
Develop semantic data models and metric definitions to ensure consistent use of features, metrics, and business rules across AI/ML solutions and BI dashboards.
Create business-facing dashboards and applications (Power BI, Streamlit) that integrate predictive or AI-driven insights for decision-makers.
Support MLOps practices by helping implement automated testing, monitoring, and model versioning within CI/CD pipelines.
Optimize data and ML environments in Snowflake and Databricks for performance, cost efficiency, and scalability of AI/ML workloads.
Ensure governance and compliance by embedding lineage, PHI/PII protection, and Responsible AI considerations into data engineering workflows, consistent with CMS and HIPAA requirements.
Actively support the achievement of SCAN’s Vision and Goals.
Other duties as assigned.

Benefits

Base Salary Range: $106,200 to $153,705 annually
An annual employee bonus program
Robust Wellness Program
Generous paid-time-off (PTO)
11 paid holidays per year, 1 floating holiday, birthday off, and 2 volunteer days
Excellent 401(k) Retirement Saving Plan with employer match
Robust employee recognition program
Tuition reimbursement
An opportunity to become part of a team that makes a difference to our members and our community every day!
A competitive compensation and benefits program;
An annual employee bonus program;
Generous paid-time-off (PTO);
Eleven paid holidays per year;
Excellent Retirement Savings program;
A work-life balance;
An opportunity to become part of a team that makes a difference to our members and our community every day!