Principle AI & Data Scientist

Alignment Health

1d • 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 AI Scientist will play a key role in designing, developing, and deploying advanced Artificial Intelligence and Machine Learning solutions to support Alignment Healthcare’s business and operational goals. This position reports to an AI Science leader within the AI organization and works closely with cross-functional partners across engineering, product, and business teams. We are seeking highly skilled AI scientists at the Principal level who are passionate about applying state-of-the-art AI and machine learning techniques to complex, real-world healthcare problems. The ideal candidate brings strong technical expertise, sound judgment, and a proven ability to translate ambiguous business challenges into scalable, production-ready AI solutions. This role requires a results-oriented mindset, intellectual curiosity, and a collaborative approach to innovation. This is a remote position within the US.

Requirements

• 8-12+ years in data science, machine learning, or AI research with a track record of high-impact contributions
• Demonstrated experience in architecting and delivering AI systems with enterprise-wide or industry-wide impact
• Proven ability to translate research into production systems that drive measurable business outcomes
• History of technical leadership: defining strategy, influencing architecture, shaping technical culture
• Track record of innovation through patents, publications, open-source contributions, or novel ML applications
• PhD in Computer Science, Machine Learning, Statistics, Applied Mathematics, or related field
• Active engagement with ML research community and continuous learning in state-of-the-art AI methods; deep knowledge of healthcare regulations, AI ethics, and responsible AI practices
• Recognized expert-level proficiency in Data Science with deep theoretical and applied knowledge across multiple domains
• Mastery of Machine Learning including supervised/unsupervised learning, deep learning, NLP, reinforcement learning, and causal inference
• Deep understanding of Generative AI, predictive modeling, and classical machine learning techniques such as boosting and random forests.
• Advanced Statistical Inference, experimental design, and ability to establish methodological standards
• Expert programming: Python, Java, SQL, or PySpark with proven ability to architect production-grade, scalable ML systems.
• Advanced SQL and experience designing data architectures for complex healthcare applications
• Deep expertise with Databricks, MLOps platforms (MLflow, Unity Catalog), and cloud-native AI systems
• Cutting-edge AI capabilities: Large language models, multimodal AI, AI agents, retrieval-augmented generation (RAG)
• Strategic understanding of healthcare business models, Medicare Advantage operations, and regulatory landscape (CMS, HIPAA)
• Exceptional communication and influence: ability to articulate AI roadmap and technical strategy to executive audiences and shape organizational direction
• Proven ability to translate technical capabilities into business value and assess technical risk, feasibility, and ROI

Nice To Haves

• Healthcare AI expertise with demonstrated impact on clinical, operational, or financial outcomes
• Medicare Advantage domain knowledge: risk adjustment, Stars, utilization management, care management
• Experience with regulatory environments: CMS, FDA, HIPAA, or AI governance
• Prior experience at leading AI-native companies or research institutions
• Track record of thought leadership: conference presentations, peer-reviewed publications, industry recognition
• Advanced training in specialized ML domains (e.g., causal inference, reinforcement learning, LLMs); executive communication and strategic leadership training
• Experience building ML platforms or infrastructure used across data science organizations
• Deep expertise in healthcare AI specialization: clinical NLP, medical imaging, risk prediction, or intervention optimization
• Multi-agent AI systems and autonomous decision frameworks
• Contributions to major open-source ML projects or industry-recognized thought leadership
• Industry recognition through certifications, awards, or fellowships in AI/ML

Responsibilities

• Define technical strategy and architect enterprise AI capabilities (35%): Partner with VP of Data Science & AI to establish technical roadmap and vision for organizational AI/ML capabilities. Architect enterprise-wide AI platforms, frameworks, and systems that enable scalable AI adoption. Drive strategic AI initiatives with enterprise-level impact such as autonomous clinical workflows, predictive member intervention engines, and AI-powered risk adjustment optimization.
• Lead innovation and advance the state of healthcare AI (25%): Research, prototype, and validate novel ML approaches that create competitive advantages. Drive proof-of-concept initiatives for cutting-edge AI technologies including LLM agents, causal inference for intervention effectiveness, and vision models for autonomous chart review. Create intellectual property through novel algorithms, proprietary methodologies, or technical frameworks.
• Influence organizational direction and technology decisions (20%): Advise executive leadership on AI strategy, technical feasibility, and risk. Shape organizational capability by influencing build-vs-buy decisions, technology stack choices, and platform investments. Partner with Engineering, Product, Clinical, and Operations leaders to embed AI into core business processes and drive enterprise alignment on technical initiatives.
• Establish technical excellence standards across the organization (10%): Set standards for code quality, MLOps maturity, model governance, and ethical AI. Own the most complex technical challenges where solutions are undefined and require significant innovation. Create reusable platforms, libraries, and tools that accelerate team productivity and raise the technical bar.
• Build external recognition and strategic partnerships (10%): Represent Alignment's technical capabilities to external stakeholders including CMS, payers, technology partners, and academic institutions. Publish research, present at conferences, and build Alignment's reputation as a leader in healthcare AI. Develop partnerships with research labs, universities, or technology vendors to advance organizational capabilities.

What This Job Offers

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