Develop and deploy scalable machine learning and AI solutions in production environments, ensuring performance and sustainability
Build and refine models for customer segmentation, risk prediction, clinical decision support, and other healthcare-specific use cases
Support cross-functional initiatives involving both traditional ML and emerging GenAI use cases
Ensure rigorous use of statistical methods, reproducibility, and documentation across all projects
Design and implement statistical tests, A/B experiments, and performance monitoring strategies
Evaluate ML/AI models and products for fairness in output, targeting and actions
Partner with stakeholders to define problem statements, identify data sources, and design effective solutions
Build and maintain robust data pipelines, modeling workflows, and monitoring tools in collaboration with engineering and data platform teams
Partner with senior and executive leadership to define and advance the enterprise AI roadmap, identifying high-impact opportunities to embed ML and AI services into core business workflows
Lead multiple high-impact data science projects across areas including Clinical, STARs, Risk Adjustment, Claims, Pharmacy, Marketing and Member Experiences
Manage and mentor a team of data scientists; provide technical guidance via review of code, models, and analytical approaches; foster professional growth; and drive a culture of experimentation and continuous learning
Requirements
Minimum 7 + years professional work experience as a data scientist, engineer or developing ML/AI solutions
5 + years of deep technical experience analyzing and modeling structured, semi-structured and unstructured data using machine learning/predictive modeling
Record of delivering ML/AI projects in production environments
Demonstrated success in hiring great data scientists and growing junior team members through mentoring, collaboration and coaching
Experience in healthcare or other highly regulated industry (preferred)
Experience with embedding approaches, vector databases and RAG (preferred)
Bachelor’s degree in Computer Science, Engineering, Statistics, or a related quantitative field (required)
Master’s or PhD in Computer Science, Engineering, Statistics, or a related quantitative field (preferred)
Up-to-date knowledge of data science related technologies and data engineering best-practices (required)
Demonstrated proficiency in SQL and relational databases (required)
Solid data structures & algorithms background (required)
Expert knowledge of analytical platforms and tools used to build and deploy Machine Learning models (required)
Excellent storytelling skills and the ability to present complex information simply in both small and large group settings to technical/non-technical audiences (required)
Benefits
Alignment Health is an Equal Opportunity/Affirmative Action Employer.
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Bachelor's degree in Computer ScienceBachelor's degree in EngineeringBachelor's degree in StatisticsMaster's degree in Computer ScienceMaster's degree in EngineeringMaster's degree in StatisticsPhD in Computer SciencePhD in EngineeringPhD in Statistics