Claims Analytics

Key Responsibilities

• Design, develop, and maintain end-to-end data pipelines for healthcare claims and enrollment data.
• Extract, consolidate, and integrate data from multiple sources, including enrollment, encounter, provider billing, and claims systems.
• Develop and implement data transformation rules, including:
• Clinical code normalization (ICD, CPT, HCPCS, DRG, etc.)
• Data type standardization
• Record deduplication
• Cross-file reconciliation
• Establish data quality, validation, and audit checkpoints to ensure data integrity and completeness.
• Identify, investigate, and resolve invalid claims, billing discrepancies, and data anomalies.
• Maintain historical data repositories and audit logs to support compliance and reporting requirements.
• Develop business rules for aggregating and analyzing claims data.
• Calculate and monitor key healthcare metrics, including:
• Loss Ratio
• Per Member Per Month (PMPM) Cost
• Claims Utilization Rate
• Average Cost per Claim
• Provider Utilization
• Claims Turnaround Time (TAT)
• Prepare dashboards, reports, and analytical summaries to support Finance, Actuarial, Operations, Provider Management, and Executive Management.
• Collaborate with cross-functional teams to define reporting requirements and improve data accuracy.
• Recommend process improvements to enhance claims analytics, reporting efficiency, and data governance.
• Ensure compliance with internal policies, healthcare regulations, and data privacy standards.

• Minimum of 3–5 years of experience in healthcare, HMO, insurance, or healthcare claims analytics.
• Experience handling large healthcare claims datasets.
• Proven experience in data extraction, transformation, and loading (ETL).
• Experience with healthcare claims processing and provider billing data.
• Experience developing analytical reports and dashboards.
• Experience performing data validation, reconciliation, and quality assurance.
• Experience working with cross-functional business stakeholders.
  
  

• Advanced proficiency in SQL for querying and data manipulation.
• Strong knowledge of Microsoft Excel (Power Query, Pivot Tables, advanced formulas).
• Experience with Power BI, Tableau, or other business intelligence tools.
• Working knowledge of Python or R for data analysis is an advantage.
• Familiarity with relational databases such as SQL Server, Oracle, PostgreSQL, or MySQL.
• Understanding of ETL concepts and data warehousing.
• Knowledge of healthcare coding standards (ICD-10, CPT, HCPCS, DRG) is an advantage.
• Strong understanding of healthcare claims lifecycle and provider reimbursement processes.