Mgr-Care Management Data Analytics

Accountabilities:: Lead the development and implementation of predictive and prescriptive analytical frameworks that support proactive decision-making and operational excellence within Care Management. Drive the transition from descriptive reporting toward predictive and prescriptive analytics to optimize workflows, anticipate risks, and improve member outcomes. Partner with Care Management leadership to identify opportunities where data science, machine learning, and advanced analytics can improve service delivery. Oversee statistical programming and machine learning approaches used to identify trends, member health risks, operational bottlenecks, and other actionable patterns. Guide the development of advanced analytical models and automated data pipelines that provide dynamic intelligence beyond traditional static dashboards. Ensure statistical methodologies and predictive models meet rigorous standards for accuracy, reliability, and scientific validity. Provide day-to-day leadership, coaching, performance management, and development for a team of data analysts. Assign and prioritize complex analytical workstreams while ensuring the team uses modern computational tools effectively. Serve as a strategic partner to IT, Business Intelligence, Quality, Clinical Operations, and other stakeholders on data architecture and advanced analytics needs. Translate complex statistical findings and technical outputs into clear, actionable recommendations for non-technical executives and leadership teams. Lead data-driven project planning, reporting initiatives, and audit preparation using predictive insights to anticipate regulatory and operational changes. Establish quality assurance protocols covering data accuracy, model integrity, algorithm reliability, and analytical consistency. Identify and mitigate risks related to data integrity, modeling quality, algorithmic bias, and responsible use of analytical outputs. Work with IT and business stakeholders to improve data capture and infrastructure for longitudinal, predictive, and advanced analytical use cases. Represent Care Management data needs across departments, clarify requirements, communicate findings, and support leadership with data-informed decisions. Ensure reports, dashboards, metrics, code, and analytical workflows are accurately documented and maintained. Requirements: Bachelor’s degree in Data Science, Statistics, Computer Science, Mathematics, or another quantitative STEM discipline with a strong focus on computational modeling and statistical analysis. 6+ years of experience in advanced data analytics or data science, including at least 2 years focused on predictive modeling, machine learning, or complex statistical programming within healthcare or a large-scale operational environment. Demonstrated experience translating business problems into clear analytical requirements and problem statements. Experience identifying, retrieving, integrating, storing, cleansing, and preprocessing data from multiple sources. Strong experience conducting exploratory data analysis and communicating analytical findings through reports, dashboards, and presentations. Proven ability to review analytical outputs for accuracy, consistency, and business relevance. Experience managing competing priorities, coordinating cross-functional stakeholders, and communicating effectively with both technical and non-technical audiences. Demonstrated ability to supervise, coach, and support data analytics or reporting professionals. Knowledge of healthcare operations, Care Management workflows, health plan performance metrics, and state reporting requirements is preferred. Experience with healthcare reporting portfolios, data warehouse reporting tools, or health plan performance metrics is an advantage. Proficiency in statistical programming languages such as R or Python for advanced data manipulation and analysis. Experience applying analytical or machine learning algorithms to identify complex patterns in healthcare, Medicaid, or Care Management data. Familiarity with machine learning frameworks and libraries such as Scikit-learn, TensorFlow, or PyTorch. Advanced SQL capabilities, including complex querying and data engineering for large-scale datasets. Strong analytical, conceptual, organizational, problem-solving, facilitation, and presentation skills. Ability to translate operational, leadership, project, and regulatory requirements into analytical work plans. Proficiency with Microsoft Excel, Microsoft Office, Teams, SharePoint, data visualization tools, and reporting platforms. Ability to represent Care Management data needs in leadership and project meetings and coordinate follow-up actions. Valid driver’s license required. Candidates must reside in North Carolina and be able to travel to the Morrisville, NC home office for onsite meetings as needed. Benefits: Full-time remote position for candidates residing in North Carolina. Opportunity to lead advanced analytics and data science initiatives within a healthcare environment. Strategic influence over predictive modeling, machine learning, data governance, and operational transformation. Leadership responsibility for developing and mentoring a team of data analysts. Cross-functional collaboration with Care Management, Clinical Operations, IT, Business Intelligence, Quality, and executive leadership. Opportunity to work with large-scale healthcare datasets, predictive models, and advanced analytical technologies. Compensation determined based on education, experience, external market data, and internal equity. Occasional travel to the Morrisville, North Carolina home office for team meetings.