Business Analytics Advisor, Payment Integrity - Healthcare - Remote

Business Analytics Advisor

We are seeking a highly motivated, forward-thinking, and innovative analytics and data science leader to join Cigna's Payment Integrity team. This role plays a critical leadership function in advancing AI-enabled analytics, automation, enterprise data initiatives, and technical modernization efforts to improve claim accuracy, scalability, and operational efficiency.

The ideal candidate brings deep expertise in data strategy, data mapping, automation, AI-assisted analytics, predictive modeling, and enterprise technology, with a strong ability to lead complex initiatives, reduce technical debt, and drive process maturity through structured, well-documented, and scalable solutions.

This role will help shape the future of Payment Integrity through advanced analytics, artificial intelligence, machine learning, automation, enterprise data strategy, and technical modernization initiatives that improve payment accuracy, reduce waste, prevent fraud, and deliver measurable business outcomes.

This position will support enterprise initiatives focused on improving claims accuracy, reducing waste and fraud, increasing transparency, and scaling impact through automation, AI-driven insights, and reusable data assets to deliver measurable financial and operational outcomes.

Key Responsibilities

Payment Integrity Analytics & Business Leadership

• Expand team expertise in external data sources and claim editing integrations to support scalable solutions.
• Standardize and format data for optimal use within claim editing programs, ensuring consistency and efficiency.
• Collaborate with the Data Analytics team to develop complex editing logic and proof-of-concept models.
• Interpret query languages using data dictionaries and facilitate translation through newly implemented editing tools and data sources.
• Lead research and updates for the Unified Claim Record (UCR) and associated data streams.
• Partner with cross-functional teams to migrate SAS-based edits to ARM (Claim Editing Platform), driving improved outcomes.
• Implement structured, data-driven processes to promote consistent and transparent claim editing practices.
• Analyze edit performance to reduce false positives and enhance claim capture accuracy.
• Document enhancement needs for claim editing and provide timely input to Scrum technical and product teams.
• Support the development and refinement of business rules and editing logic to align with evolving business needs.
• Collaborate with matrixed business partners to define data requirements, identify improvement opportunities, and communicate analytical findings and solutions effectively.
• Drive enterprise data initiatives focused on improving data quality, governance, traceability, and operational effectiveness.
• Support technical modernization efforts through automation, reusable assets, process standardization, and improved analytical capabilities.

Data Science, AI & Advanced Analytics

• Develop and apply statistical models, predictive analytics, and machine learning techniques to identify patterns, trends, anomalies, and opportunities within healthcare claims data.
• Design, evaluate, and operationalize AI-enabled and data science solutions that improve payment accuracy, reduce false positives, and enhance claim editing performance.
• Perform exploratory data analysis on complex healthcare datasets to uncover actionable insights and develop data-driven recommendations.
• Collaborate with data engineering and technology teams to build scalable analytical solutions and reusable data assets.
• Evaluate emerging AI, machine learning, and healthcare analytics technologies to identify opportunities for innovation within Payment Integrity.
• Support development of proof-of-concept models, pilot initiatives, and advanced analytical frameworks to validate business value and scalability.
• Design and execute model validation, performance monitoring, and outcome measurement approaches to ensure analytical solutions deliver expected results.
• Develop dashboards, visualizations, and executive-level reporting that communicate analytical findings to both technical and non-technical audiences.
• Partner with business stakeholders to transform…