Senior Data Analyst - AI & Dermatology Claims Analytics

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.