RCM Data Analyst

Labcorp is a global leader in laboratory services, providing the insights and answers that help healthcare providers, patients, researchers, pharmaceutical companies and health systems make confident decisions and improve outcomes. Through our unparalleled science, data, technology and laboratory network, we advance diagnostics, accelerate innovation and help address some of the world's most important health challenges. As we shape the future of healthcare, we are leveraging advanced technologies, intelligent digital solutions and data-driven innovation across our operations to enhance how work gets done and deliver greater value to customers and patients. With our global scale and deep expertise, you'll have the opportunity to do meaningful work, grow your career and make a real impact on people's health around the world. Together, we're improving health and improving lives., This hybrid position offers a balanced schedule of three in-office workdays at our Burlington or Durham, NC locations and two remote workdays per week, supporting both collaboration and flexibility., Data Analysis & Research

• Develop and execute large-scale analytical studies utilizing claim-level, laboratory, billing, and reimbursement data to support Revenue Cycle Management (RCM) initiatives.
• Analyze claim lifecycle data from order entry through post-adjudication activities to identify reimbursement opportunities, process gaps, and revenue optimization strategies.
• Locate, validate, integrate, and analyze data from multiple systems and sources, including laboratory systems, billing platforms, payer transactions, government policies, and internal databases.
• Apply payer policy requirements, reimbursement guidelines, and claim transaction data to identify trends impacting claim outcomes and payment performance.
• Perform statistical sampling, predictive modeling, and trend analysis to support operational decision-making and risk mitigation efforts.

Reporting & Business Insights

• Locate, validate and analyze data using SAS, SQL, Access, VBA and Tableau and other reporting tools.
• Translate analytical findings into actionable recommendations that support process improvements, reimbursement optimization, and revenue protection initiatives.
• Create monitoring models and alerting mechanisms to identify process deviations, reimbursement risks, and system performance issues.
• Deliver analysis and reporting that supports business prioritization, operational improvements, and strategic initiatives.

Systems Controls & Business Rules

• Support system control research and monitoring efforts to reduce revenue leakage and improve reimbursement outcomes.
• Evaluate system workflows, payer policies, and claim processing rules to identify opportunities for technology enhancements and business rule modifications.
• Recommend and support development of business rules associated with system changes, automation efforts, and revenue cycle technologies.
• Conduct testing and validation activities associated with system enhancements and process modifications.

Industry & Organizational Support

• Support RCM Policy initiatives related to payer engagement, acquisitions, industry workgroups, and reimbursement process improvements.
• Develop analyses utilizing industry-standard data sources to support business solution initiatives and payer-related projects.
• Participate in cross-functional discussions regarding reimbursement policies, claim processing strategies, and operational initiatives., The Senior RCM Data Analyst supports Revenue Cycle Management initiatives through advanced data analytics, reimbursement research, and operational insights. This role combines data from laboratory, billing, claims, payer, and policy sources to identify opportunities that improve reimbursement outcomes, reduce revenue leakage, and enhance system performance. The position partners with business leaders and cross-functional teams to deliver analytical solutions, influence process improvements, and support strategic revenue cycle initiatives through data-driven decision making.

• Bachelor's degree in Statistics, Mathematics, Informatics, Computer Science, Information Systems, or a closely aligned quantitative field with 6 or more years of experience; with
• 5 or more years of experience performing data analytics within healthcare, revenue cycle management, reimbursement, payer operations, laboratory services, or billing environments.
• 5 or more years of experience using SQL for querying, data validation, transformation, and analysis of large datasets.
• 3 or more years of experience utilizing SAS for statistical analysis, data management, and reporting.

Preferred Qualifications

• Master's degree in Statistics, Mathematics, Informatics, Computer Science, Information Systems, or a closely aligned quantitative field with 4 or more years of experience.
• 7 or more years of experience performing advanced healthcare, reimbursement, or revenue cycle analytics.
• 5 or more years of experience analyzing payer policy requirements, claim adjudication processes, and healthcare reimbursement transactions.
• 2 or more years of experience working with laboratory information systems, billing systems, or healthcare claims processing platforms.

Additional Job Standards

• Experience supporting revenue cycle optimization, denial reduction, reimbursement improvement, or revenue integrity initiatives.
• Experience developing predictive analytics, statistical models, or anomaly detection solutions.
• Experience performing statistical sampling, modeling, forecasting, or trend analysis.
• Experience analyzing claim-level healthcare, laboratory, billing, reimbursement, or adjudication data.
• Experience developing business rules, system controls, monitoring models, or automated alerting processes.
• Experience integrating and validating data from multiple operational and transactional systems.
• Experience supporting healthcare acquisitions, payer initiatives, or industry workgroup projects through analytics and reporting.
• Experience utilizing Microsoft Excel and VBA for automation, reporting, and data analysis.
• Demonstrate effective communication of analytical findings to business, operational, and leadership stakeholders.
• Collaborate with cross-functional teams to support strategic business objectives and operational initiatives.
• Apply critical thinking, curiosity, and problem-solving approaches when evaluating complex business and reimbursement challenges.
• Contribute to team discussions and facilitate knowledge sharing related to analytical methods, processes, and best practices.
• Present complex analytical findings in a manner that supports organizational decision-making and change management efforts.
• Support team development through mentoring, knowledge transfer, and sharing of analytical techniques.
• Maintain attention to detail while validating data accuracy, analytical methodologies, and reporting outputs.
• Demonstrate knowledge of healthcare reimbursement processes, payer policies, claim lifecycles, and revenue cycle operations.