Sr. AI & Data Scientist

Alignment Health • Washington, DC

2d • $172,364 - $258,547 • Remote

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 Sr. AI Scientist combines deep analytical expertise with advanced software engineering skills to architect and deliver high-impact AI/ML solutions on our proprietary clinical intelligence platform. This role owns complex, ambiguous problems from discovery to production deployment, drive technical excellence across the team, and mentor data scientists while partnering with engineering, product, and clinical leaders to deliver measurable outcomes for Medicare Advantage members.

Requirements

• Experience Required: 5-8 years delivering production-grade data science or ML solutions with demonstrated business impact
• Proven track record architecting complex ML systems from research to production deployment
• Deep expertise in multiple ML domains and strong software engineering fundamentals
• Experience leading technical projects and mentoring data scientists
• Education Required: PhD in Computer Science, Machine Learning, Statistics, or related field
• Training Required: Continuous learning in ML/AI advancements, healthcare analytics, and software engineering practices
• Specialized Skills Required: Expert-level proficiency in Data Science methods, workflows, and best practices
• Advanced Machine Learning including ensemble methods, deep learning, NLP, LLMs, and computer vision
• Strong Statistical Analysis and experimental design capabilities
• Expert programming: Python, Java, SQL, or PySpark with an emphasis on production-grade, maintainable code.
• Advanced SQL and experience with high-volume, high-dimensional healthcare data
• Proficiency with Databricks (Spark, Delta Lake), MLflow, Unity Catalog, and cloud platforms
• Experience with Git workflows, CI/CD pipelines, Docker, and modern MLOps practices
• Deep understanding of healthcare data (claims, clinical, member) and Medicare Advantage operations
• Exceptional communication skills: ability to translate technical complexity into business value for diverse stakeholders
• Strong data visualization and storytelling capabilities with proven ability to influence technical decisions

Nice To Haves

• Healthcare domain expertise, particularly Medicare Advantage, risk adjustment, or claims analytics
• Experience with production document understanding systems (OCR, NER, entity extraction, LLM pipelines)
• Published research, open-source contributions, or patents in ML/AI
• Track record of translating research innovations into production systems
• Training or certification in MLOps, cloud platforms (Azure, AWS, GCP), or healthcare regulations (HIPAA, CMS)
• Experience with NoSQL databases, performance optimization, and distributed computing
• Real-time ML inference and streaming architectures
• Contributions to internal ML platforms, frameworks, or open-source projects
• Experience presenting at technical conferences or publishing research

Responsibilities

• Architect end-to-end AI/ML solutions for complex healthcare challenges (35%): Design and deliver production-grade machine learning systems for high-stakes applications including risk stratification, clinical decision support, autonomous chart review, and fraud detection. Define technical approach, model selection, and system architecture for multi-model systems and real-time decision engines that process millions of healthcare transactions.
• Own the full ML lifecycle from experimentation to production (25%): Build reliable, scalable AI services including experimentation, validation, deployment, monitoring, drift detection, and continuous improvement. Establish instrumentation, observability, alerting, and feedback loops to ensure model performance and reliability in production environments.
• Drive technical excellence and innovation (15%): Research and apply state-of-the-art methods in deep learning, NLP/LLMs, computer vision, and causal inference to healthcare problems. Champion engineering best practices including code quality, testing, documentation, reusability, and maintainability across the data science organization.
• Partner strategically with cross-functional leaders (15%): Collaborate with Product, Clinical, Operations, and Compliance teams to identify high-value AI opportunities aligned with business strategy. Translate complex technical concepts into clear business narratives for executive audiences and influence product roadmap and technology decisions.
• Provide technical mentorship and raise the bar (10%): Guide data scientists through code reviews, architectural discussions, and pair programming. Share knowledge through internal presentations and documentation. Support hiring by conducting technical interviews and modeling best practices in analytical rigor and problem-solving.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: Ph.D. or professional degree
• Number of Employees: 1-10 employees