About Alignment Health
Alignment Health is committed to serving seniors and the chronically ill and frail. We are dedicated to transforming healthcare by putting the senior first. We have built a team of talented and experienced people passionate about making a difference. Working at Alignment Health provides an opportunity to do work that matters, changing and saving lives.
About the Role
The Data Scientist will combine deep analytical expertise with production‑grade software development skills to build reliable, scalable solutions on our proprietary clinical intelligence platform. You will own initiatives from problem framing to model delivery and partner with software and data engineering partners to deploy into production environments.
We are seeking a mission-driven Data Scientist to join our growing team and support risk adjustment strategy within our Medicare Advantage line of business. This role focuses on enhancing risk score accuracy, CMS audit preparedness (RADV), and building AI-powered tools that improve clinical documentation review and integrity.
You’ll play a key role in advancing AVA, our proprietary clinical intelligence platform, by developing next-generation models that support autonomous chart review and NLP/GenAI-driven documentation analytics. This is a unique opportunity to work at the intersection of healthcare, compliance, and machine learning—transforming how we ensure both quality and regulatory alignment.
Job Duties/Responsibilities
- Own end‑to‑end solutions: translate ambiguous healthcare and operational problems into AI/ML models that deliver measurable impact by selecting methods, building data/models, deploying services, instrumenting observability, and real-world feedback loops.
- Partner with Product, Engineering, and Clinical leaders to embed data science into workflows like claims processing, utilization management, provider network optimization, risk adjustment, etc.
- Deliver clinical intelligence features such as autonomous chart review, disease detection, compliance forecasting, and quality analytics.
- Build AI/NLP/LLM models for document understanding and information extraction, including OCR, NER, and vision models.
- Advance quality and payment integrity: create models and automated QA to reduce manual review, increase accuracy, and surface documentation anomalies and audit risk.
- Champion engineering excellence: internal libraries, reusable components, coding standards, code reviews, and clear documentation.
- Own the lifecycle: monitoring, drift detection, alerting, and post‑deployment reviews.
Requirements
Experience
- 2-5 years delivering production‑grade data science or ML software with measurable impact.
- Strong software engineering fundamentals: data structures, algorithms, modular design, API design, documentation.
- Proficiency in Python plus SQL; experience building reusable packages, utilities, and CLI tools.
- Applied knowledge of ML (tree ensembles, boosting, NLP/LLMs, deep learning) and experimental design.
- Experience with high‑volume, high‑dimensional, and unstructured data; strong data quality mindset.
- Experience with Git workflows, code reviews, CI/CD.
- Excellent data visualization and storytelling skills.
- Ability to thrive in ambiguous, fast‑paced environments.
Preferred Qualifications
- Healthcare domain experience; familiarity with CMS/Medicare Advantage operations.
- Document understanding systems with OCR/NER and LLM pipelines.
- Experience with NoSQL and performance optimization.
- Contributions to internal frameworks or open‑source; published work.
Education
- Required: Bachelor’s degree in Computer Science, Data Engineering or similar technical field.
- Preferred: MSc/PhD in CS, Engineering, Math, Statistics, or related field.
Specialized Skills
- Python, SQL
- Databricks (Spark, Delta Lake)
- MLflow, Unity Catalog, Git, CI/CD, Docker
- REST/GraphQL APIs, orchestration
- NLP/LLM & Vision: OCR, NER, embeddings
- Ability to communicate positively, professionally and effectively with others; provide leadership, teach and collaborate with others.
- Effective written and oral communication skills; ability to establish and maintain a constructive relationship with diverse members, management, employees and vendors;