Cano Health is seeking a Senior Data Scientist to leverage advanced analytics, machine learning, and statistical modeling to transform complex healthcare data into actionable insights that improve clinical outcomes, reduce costs, and optimize population health strategies.
Requirements
- Proven experience with supervised (e.g., logistic regression, gradient boosting, neural networks) and unsupervised techniques (e.g., clustering, PCA) applied to healthcare use cases.
- Strong SQL and Python skills with hands-on experience in healthcare data sources such as claims, EHRs, labs, pharmacy, or care management platforms.
- Experience supporting Accountable Care Organizations (ACOs), Medicare Advantage plans, or Medicaid managed care.
- Deep understanding of risk adjustment methodologies (e.g., CMS-HCC), quality measures (e.g., HEDIS, CAHPS), and social determinants of health.
- Experience developing Power BI dashboards integrated with healthcare databases or population health tools to support executive-level reporting.
- Knowledge of value-based care KPIs such as total cost of care, utilization metrics, quality bonus programs, or shared savings.
- Familiarity with healthcare regulatory and compliance frameworks (e.g., HIPAA)
Responsibilities
- Analyze and interpret large volumes of healthcare data (structured and unstructured), including claims, clinical, operational, and patient-reported data to generate actionable insights.
- Develop and validate predictive and prescriptive models that support care management, population health, utilization forecasting, and performance in value-based contracts (e.g., ACOs, Medicare Advantage, MSSP, commercial risk).
- Perform advanced feature engineering and exploratory data analysis to identify risk drivers, trends, and opportunities for intervention.
- Build and deploy risk stratification algorithms, such as models for predicting hospital readmissions, emergency department utilization, gaps in care, or progression of chronic conditions.
- Create compelling data visualizations, dashboards, and storytelling tools that communicate complex information to clinical and non-technical audiences.
- Design and automate continuous model evaluation frameworks to ensure the long-term relevance and fairness of models across diverse patient populations.
- Collaborate with product, engineering, and IT teams to ensure clean, scalable, and reproducible analytics pipelines using modern tools and cloud platforms.
Other
- 8+ years of experience in advanced analytics, statistical modeling, or data science, ideally within a healthcare or payer/provider context.
- Master’s degree in statistics, mathematics, computer science, health informatics, or a related quantitative field is preferred.
- Strong interpersonal and communication skills to translate technical results into operational strategies for diverse stakeholders including clinicians, executives, and payers.
- Background in epidemiology, clinical decision support, or public health analytics.
- Ability to work extended and flexible hours and weekends as needed.
