[Hiring] Manager - Care Management Data Analytics @Alliance Health

Role Description

The Manager- Care Management Data Analytics leads the development of predictive and prescriptive analytical frameworks to drive operational excellence. This position directs the application of machine learning and advanced statistical programming to transform Care Management data into actionable business intelligence. This position is full-time remote. Selected candidate must reside in North Carolina and be willing to travel to the home office (Morrisville, NC) for onsite team meetings as needed.

Responsibilities & Duties

• Strategic Data Leadership & Operational Transformation
  • Direct the development and implementation of advanced analytical frameworks to drive proactive business decision-making and operational excellence within Care Management.
  • Lead the transition from descriptive reporting (what happened) to predictive and prescriptive analytics (what will happen and what we should do) to optimize Care Management workflows and member outcomes.
  • Partner with Care Management leadership to identify strategic opportunities where data science and machine learning can mitigate risks and improve service delivery.
• Advanced Analytics & Predictive Modeling Oversight
  • Oversee the application of statistical programming and machine learning methodologies to identify trends, member health risks, and operational bottlenecks.
  • Manage the development of sophisticated analytical models and automated data pipelines that move beyond static dashboards to dynamic, real-time intelligence.
  • Ensure the rigor of advanced statistical methodologies used by the team to maintain high standards of predictive accuracy and scientific validity.
• Data Analyst Team Leadership & Talent Development
  • Provide day-to-day oversight, coaching, and performance management for a team of data analysts.
  • Assign, prioritize, and manage complex analytical workstreams, ensuring the team is utilizing modern computational tools to meet organizational goals.
• Cross-Functional Strategic Partnership
  • Act as a strategic consultant to IT, Business Intelligence, Quality, and Clinical Operations to ensure data architecture and infrastructure support high-level advanced analytics.
  • Translate complex technical findings and statistical model outputs into clear, actionable strategic recommendations for non-technical executive leadership.
  • Lead data-driven project planning and audit preparations, utilizing predictive insights to anticipate regulatory or operational shifts.
• Data Governance & Advanced Quality Assurance
  • Establish and oversee advanced quality assurance protocols that validate not only data accuracy but also the integrity and reliability of complex statistical models and algorithms.
  • Identify and mitigate risks related to data modeling, algorithmic bias, and data integrity to ensure robust and ethical decision-making.
  • Coordinate with IT and stakeholders to ensure that data capture processes are optimized for high-level longitudinal and predictive analysis.
• General Management and Administrative Duties
  • Serve as a liaison between Care Management and other departments to clarify requirements and communicate data findings.
  • Support leadership with data-informed decision-making, project planning, and response to internal or external reporting needs.

Qualifications

• Education & Experience
  • Required: Bachelor's degree in Data Science, Statistics, Computer Science, Mathematics, or a quantitative STEM field from an accredited college/university with a proven focus on computational modeling and statistical analysis.
  • Six (6) years of experience in advanced Data Analytics or Data Science, with at least two (2) years specifically focused on developing predictive models, implementing machine learning algorithms, or performing complex statistical programming within a healthcare or large-scale operational environment.
  • Experience must include translating business needs into analytic requirements, reviewing reports for accuracy, communicating findings to leadership, managing competing priorities, and coordinating with technical and non-technical stakeholders.
• Preferred:
  • Experience supervising analytic staff, managing healthcare reporting portfolios, and participating in leadership or project governance meetings.
  • Experience working with health plan performance metrics, state reporting, and data warehouse reporting tools.
  • Participation in certified, instructor-led courses in Data Management, Advanced Data Analytic Methodology, and Digital Presentation.

Requirements

• Demonstrated ability to supervise, coach, support, and manage analytic or reporting staff.
• Ability to validate analyst reports, dashboards, metrics, and data outputs for accuracy and consistency.
• Knowledge of healthcare operations, Care Management workflows, health plan performance metrics, and state reporting requirements.
• Ability to translate leadership, operational, project, and regulatory needs into reporting requirements and analytic work plans.
• Strong leadership, communication, facilitation, and presentation skills for technical and non-technical audiences.
• Ability to attend leadership and project meetings, represent Care Management data needs, and coordinate follow-up actions.
• Strong analytical, conceptual, organizational, and problem-solving skills.
• Ability to manage competing priorities, escalations, deadlines, and cross-functional stakeholder expectations.
• Computer proficiency in Microsoft Excel, Microsoft Office Suite, Teams, SharePoint, data visualization tools, and reporting platforms.
• Statistical Programming: Proficiency in languages like R or Python for advanced data manipulation.
• Application of algorithms to identify complex patterns in Medicaid or Care Management data.
• Machine Learning Frameworks: Familiarity with libraries such as Scikit-learn, TensorFlow, or PyTorch.
• Advanced SQL: Experience in complex data engineering and querying for large-scale datasets.

Benefits

• Exact compensation will be determined based on the candidate's education, experience, external market data, and consideration of internal equity.