Data Scientist

Alignment Health

1d • $149,882 - $224,823

About The Position

Alignment Health is breaking the mold in conventional health care, committed to serving seniors and those who need it most: the chronically ill and frail. It takes an entire team of passionate and caring people, united in our mission to put the senior first. We have built a team of talented and experienced people who are passionate about transforming the lives of the seniors we serve. In this fast-growing company, you will find ample room for growth and innovation alongside the Alignment Health community. Working at Alignment Health provides an opportunity to do work that really matters, not only changing lives but saving them. Together. 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 au-dit preparedness (RADV), and building AI-powered tools that improve clinical documentation review and integ-rity. 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.

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.
• Required: 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;

Nice To Haves

• 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.
• Preferred: MSc/PhD in CS, Engineering, Math, Statistics, or related field.

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.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level