Business Analytics Advisor, Payment Integrity - Cigna Healthcare - Remote

The Cigna Group is dedicated to improving health and vitality through innovative solutions. They are seeking a Business Analytics Advisor for their Payment Integrity team to lead advanced analytics and data science initiatives that enhance claim accuracy and operational efficiency.

Responsibilities:

• 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
• 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 operational challenges into analytical hypotheses and measurable data science initiatives
• Promote responsible AI practices through governance, data quality management, transparency, model explainability, and compliance-focused solution design
• Leverage AI-assisted analytics, natural language processing, and emerging technologies to improve operational efficiency and decision support
• Identify opportunities to automate manual processes, reduce operational complexity, and accelerate analytical insight generation

Requirements:

• Demonstrated advanced proficiency with at least 3 years of hands-on experience in data mining, analysis, and processing using tools and languages such as SAS, Altair, SQL, TOAD, Python, R, or comparable technologies
• Bachelor's degree in Business Analytics, Data Science, Information Systems, Computer Science, Statistics, Applied Mathematics, Healthcare Informatics, or a related field preferred
• 7+ years of experience in data analytics, data science, business intelligence, or related analytical disciplines, preferably within healthcare or claims processing
• Proven ability to extract actionable insights using advanced data mining techniques and business intelligence tools to support strategic decision-making
• Strong analytical skills with the ability to translate complex data into meaningful, actionable insights
• Adept at leveraging analytical tools to explore and interpret complex healthcare data, conduct root cause analyses, and deliver actionable insights through clear, data-driven reporting
• Experience applying statistical analysis, predictive modeling, and quantitative problem-solving techniques to complex business challenges
• Strong understanding of machine learning concepts, model development lifecycle, feature engineering, model evaluation, and performance monitoring
• Experience working with large-scale structured and unstructured datasets to identify trends, patterns, risks, and opportunities
• Strong knowledge of data visualization and storytelling techniques utilizing Power BI, Tableau, Python visualization libraries, or similar tools
• Experience in healthcare or managed care environments with direct responsibility for data analysis, data management, and relational database concepts
• Deep understanding of healthcare data and the health delivery system
• Ability to translate analytical findings into business recommendations and influence strategic decision-making
• Excellent communication, presentation, and collaboration skills with the ability to work effectively across technical and business teams
• Master's degree in Data Science, Statistics, Computer Science, Applied Mathematics, Analytics, Healthcare Informatics, or a related quantitative discipline
• Experience with rule-based editing platforms and healthcare claims editing technologies
• Familiarity with healthcare claims data and Payment Integrity principles
• Advanced knowledge of provider reimbursement methodologies
• In-depth understanding of Cigna data sources and integration strategies
• Experience applying machine learning, predictive analytics, artificial intelligence, natural language processing (NLP), or advanced statistical methodologies within healthcare environments
• Familiarity with cloud-based analytics platforms such as Databricks, Azure, AWS, Snowflake, or similar technologies
• Experience developing, validating, deploying, and monitoring analytical models in production environments
• Knowledge of healthcare fraud, waste, and abuse detection methodologies and predictive claim analytics
• Experience supporting AI governance, model risk management, data quality, and responsible AI initiatives
• Experience working with Large Language Models (LLMs), Generative AI, Retrieval-Augmented Generation (RAG), AI assistants, or intelligent automation solutions
• Familiarity with healthcare interoperability standards, enterprise healthcare data ecosystems, and modern data architecture principles