Business Analytics Advisor, Payment Integrity
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Job Description
Business Analytics Advisor at Cigna focusing on AI-enabled analytics and automation to enhance claim accuracy and reduce fraud. Leading complex initiatives with advanced data science techniques.
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.
Benefits:
- Health insurance
- 401(k)
- Company paid life insurance
- Tuition reimbursement
- Minimum of 18 days of paid time off per year
- Paid holidays
- Leaves of absence
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