SENIOR DATA ANALYST – AI & DERMATOLOGY CLAIMS ANALYTICS

Comprehensive Position Description

Reporting Structure

• Dual reporting relationship: Technical reporting to Chief Information Officer; Functional reporting to Vice President of FP&A.
• Acts as liaison between IT, Finance, Revenue Cycle, Clinical Operations and Executive Leadership.

Position Summary

• Lead analytics initiatives involving large dermatology claims, EMR, revenue cycle and operational datasets.
• Leverage AI tools and advanced analytics to improve reimbursement, forecasting and operational performance.

Primary Responsibilities

• Analyze millions of claims records across CPT, HCPCS, ICD-10, payer and provider dimensions.
• Identify revenue leakage, denial trends, coding opportunities and reimbursement optimization opportunities.
• Develop AI-assisted analytical workflows using Copilot, Azure AI and LLM technologies.
• Build executive dashboards and KPI reporting.
• Support budgeting, forecasting and strategic planning initiatives.
• Partner with managed care on payer contract performance analytics.

Technical Requirements

• Advanced SQL
• Python
• Power BI
• Microsoft Fabric
• Azure Data Services
• Databricks or Snowflake
• Healthcare data warehousing
• Machine learning and predictive analytics

Healthcare Domain Expertise

• Dermatology claims analytics
• Revenue cycle management
• Medical coding
• Payer reimbursement methodologies
• Provider productivity analytics
• Value-based care and population health

AI Competencies

• Prompt engineering
• Generative AI assisted reporting
• Predictive analytics
• Anomaly detection
• Natural language processing
• Model validation and governance

Key Performance Indicators

• Reimbursement improvement opportunities identified
• Dashboard adoption
• Forecast accuracy
• Reduction in manual reporting effort
• Denial trend visibility
• Executive stakeholder satisfaction

Qualifications

• Bachelor degree in quantitative discipline required.
• Masters degree preferred.
• 5 years healthcare analytics experience preferred.
• Experience with large healthcare claims datasets required.