Lead Risk Adjustment Data Science Manager

Mosaic Health, LLC.; New York (NY); On-site; USD 138,000 - 207,000; Full time

Job summary

Mosaic Health, LLC. in New York, NY is seeking a Manager, Risk Adjustment Data Science to drive advanced analytics and ML-driven solutions for clinical and business challenges.

You will lead end-to-end data science projects, collaborate with data engineering and business partners, and ensure enterprise readiness of models and insights. The role emphasizes problem framing, model deployment, and strategic recommendations for senior leadership, with opportunities to mentor a growing data science

Qualifications

• Own the development and productionization of advanced machine learning models and analytical frameworks addressing complex business and clinical problems.
• Lead end-to-end data science projects from problem framing through model deployment with cross-functional coordination.
• Design experiments, evaluation frameworks, and model validation approaches to ensure performance and business impact.
• Serve as the primary data science resource translating findings into strategic recommendations for senior leadership.
• Identify opportunities to apply data science methods to unaddressed problems and develop business cases for new initiatives.
• Establish and maintain best practices for model documentation, version control, and performance monitoring.

Responsibilities

• Own development and productionization of ML models and analytical frameworks.
• Lead end-to-end data science projects from problem framing to deployment.
• Design experiments and validation approaches to meet performance thresholds.
• Mentor and guide data scientists and analysts to elevate the team's capabilities.

Skills

Advanced analytics

Machine learning

Statistical modeling

Experiment design

Data wrangling

Job description

Mosaic Health, LLC. in New York, NY is seeking a Manager, Risk Adjustment Data Science to drive advanced analytics and ML-driven solutions for clinical and business challenges.

You will lead end-to-end data science projects, collaborate with data engineering and business partners, and ensure enterprise readiness of models and insights. The role emphasizes problem framing, model deployment, and strategic recommendations for senior leadership, with opportunities to mentor a growing data science