Senior AI & Data Scientist

Alignment Health

. Architect end-to-end AI/ML solutions for complex healthcare challenges, including risk stratification, clinical decision support, autonomous chart review, and fraud detection .

Posted 10/11/2026full-timeRemote • United StatesSenior💰 $172,364 - $258,547 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in architecting and delivering production-grade AI/ML solutions in healthcare, with a strong focus on advanced machine learning techniques, data science best practices, and effective collaboration across multidisciplinary teams.

Highest-signal resume keywords

Machine Learning SolutionsDeep LearningStatistical AnalysisPython ProgrammingHealthcare Data Expertise

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningData ScienceStatistical AnalysisExperimental DesignDeep LearningNatural Language ProcessingComputer VisionEnsemble MethodsProduction DeploymentData Visualization

Soft Skills

Exceptional CommunicationMentoringCollaborationProblem-SolvingStorytelling

Tools & Technologies

DatabricksSparkDelta LakeMLflowUnity CatalogCloud PlatformsGitCI/CD PipelinesDockerMLOps

Industry Keywords

Healthcare AnalyticsMedicare Advantage OperationsAI OpportunitiesTechnical ProjectsProduction-Grade Systems

Tech Stack

Tools & technologies

CloudDockerJavaPySparkPythonSparkSQLUnity

About the role

Key responsibilities & impact

Architect end-to-end AI/ML solutions for complex healthcare challenges, including risk stratification, clinical decision support, autonomous chart review, and fraud detection
Design and deliver production-grade machine learning systems processing millions of healthcare transactions
Own the full ML lifecycle from experimentation and validation through deployment, monitoring, drift detection, and continuous improvement
Establish instrumentation, observability, alerting, and feedback loops for production model performance and reliability
Research and apply state-of-the-art deep learning, NLP/LLMs, computer vision, and causal inference methods
Champion engineering best practices including code quality, testing, documentation, reusability, and maintainability
Collaborate with Product, Clinical, Operations, and Compliance teams to identify high-value AI opportunities
Translate technical concepts into business narratives for executive audiences and influence product and technology decisions
Mentor data scientists through code reviews, architectural discussions, pair programming, presentations, and documentation
Conduct technical interviews and model best practices in analytical rigor and problem-solving

Requirements

What you’ll need

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
PhD in Computer Science, Machine Learning, Statistics, or related field
Continuous learning in ML/AI advancements, healthcare analytics, and software engineering practices
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 in Python, Java, SQL, or PySpark, emphasizing 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 and Medicare Advantage operations
Exceptional communication skills to translate technical complexity into business value
Strong data visualization and storytelling capabilities
Required licensure: None