Head of Informatics
Company:Chamber Cardio
Location:United States
Languages:English
Seniority level:Lead, 10+ years
Experience:10+ years
Skills:
LeadershipProject ManagementPythonSQLArtificial IntelligenceData AnalysisMachine LearningSoftware ArchitectureCross-functional Team LeadershipProduct DevelopmentStrategyData scienceMentoringData modeling
Requirements:
- 10+ years in bioinformatics, data science, or advanced analytics in a healthcare field
- 5+ years working in value-based care environments
- Strong applied data science and statistics skills including predictive modeling, risk scoring, recommendation techniques, and observational study design
- Proficiency in Python or R and SQL
- Experience evaluating and monitoring models (AUC, calibration, lift, stability/drift)
- Hands-on experience with large healthcare datasets and converting them into production features and models
- Experience designing clinical data models, cohorts/registries, and clinical decision support or rules engines
- Proven ability to translate clinical and operational requirements into production-ready data and workflow logic with engineering teams
Responsibilities:
- Set and own the informatics and data science roadmap aligned to cardiology VBC outcomes
- Lead cross-functional efforts with Clinical, Operations, Product, and Engineering
- Communicate model and rules-engine performance, risks, and roadmap to executives and clinical leaders
- Define and maintain unified clinical concepts, cohorts, and event definitions
- Architect and refine the rules engine for cardiology programs
- Translate clinical program design into executable rules, scores, and triggers
- Lead design and development of a recommendation engine for patients and providers
- Own the applied data science strategy and partner with Data Science/ML and Engineering to deploy models
- Monitor performance and iterate based on outcomes and clinician feedback
- Define processes and standards for informatics and data science work
- Partner with Engineering/MLOps on analytics and ML infrastructure requirements
- Recruit and mentor a team of informaticists, analysts, and data scientists
