Senior Data Analyst - AI & Dermatology Claims Analytics
Advanced Dermatology and Cosmetic Surgery · Maitland, Florida, United States
11-50 employees
About the role
Lead analytics initiatives involving large dermatology claims, EMR, and revenue cycle datasets to improve operational performance. Develop AI-assisted analytical workflows and build executive dashboards to support strategic planning and forecasting.
What they look for
Requirements
Requires a bachelor degree in a quantitative discipline and 5+ years of healthcare analytics experience. Proficiency in SQL, Python, Power BI, and experience with large healthcare claims datasets is essential.
Full description
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.
