Data Scientist

Community Care of North Carolina Inc•Garner, NC

5d•Onsite

About The Position

As a Data Scientist at CCNC, you will build and maintain predictive models that support our proprietary Impactability™ framework, which identifies Medicaid patients most likely to benefit from care management outreach. You will analyze large claims, clinical, and social determinants of health datasets to surface trends, disparities, and opportunities for population health improvement. You will collaborate closely with clinical, care management, and network teams to translate analytic findings into practical program recommendations. You will also contribute to the continued development of CCNC's cloud-based analytics infrastructure on AWS, design and run retrospective and prospective program evaluations, and prepare clear data visualizations and reports for both technical and non-technical audiences including executive leadership, payers, and state partners. Additionally, you will support quality improvement initiatives by developing performance metrics and benchmarking tools used by practices across the state.

Requirements

Master's degree or higher (PhD preferred) in Data Science, Biostatistics, Epidemiology, Health Informatics, Computer Science, or a related field (or equivalent professional experience)
3+ years of experience applying machine learning and statistical modeling to real-world problems
Experience working with large, complex datasets — ideally administrative claims, EHR data, or other healthcare data
Strong SQL skills and comfort working in cloud environments (AWS preferred)
Strong skills using any statistical software package
Ability to communicate technical findings clearly to non-technical stakeholders
Demonstrated commitment to equity and improving outcomes for underserved populations

Nice To Haves

Experience with Medicaid or other public payer data
Background in program evaluation or applied health services research
Familiarity with population health management concepts and care management workflows

Responsibilities

Build and refine machine learning models for our proprietary predictive models
Design and implement a framework for continuous model improvements for both our Risk and Impactability predictive models
Evaluate models for potential bias and implement appropriate corrections
Build New predictive models that address emerging business needs
Incorporate novel data sources (e.g., clinical data) and variables into the models
Update and maintain the table of look-up values that contribute to our models
Monitor and validate the production of algorithms and predictive models within our population health analytics application (Innovaccer)
Help design and implement evaluations of CCNC programs
Present and summarize the results of CCNC program evaluations
Help develop and implement performance metrics and associated benchmarks
Help the enterprise identify drivers and actionable solutions for reducing total cost of care for our value-based contracts
Other duties as required