📋 Description

• Design, train, validate, refine ML models for fraud risk
• Develop labeling and entity-resolution approaches
• Design validation for delayed labels and imbalanced data
• Engineer features on large claims datasets with SQL/Python
• Provide ranked risk scores and supporting evidence
• Deploy models with monitoring and versioning

🎯 Requirements

• Master's in a quantitative field or bachelor’s with experience
• 5+ years building supervised ML models with real-world data
• Production deployment experience with scheduling and monitoring
• Strong Python and SQL, large-scale data warehouse experience
• 2+ years healthcare claims data experience (ICD-10, CPT, HCPCS, DRG)
• Ability to explain complex outputs to non-technical users

🎁 Benefits

• Salary: $123,250–$166,750 per year
• Fully remote with standard 40-hour week
• Health, retirement, and paid time off benefits
• Family/personal leave and leave options
• Disability, life, and travel insurance
• Full-flex work arrangements for work-life balance