Data Scientist Healthcare Fraud Waste and Abuse Analytics
Role details
Job location
Tech stack
Job description
Novacis Digital is seeking a highly technical and creative Data Scientist with over 10+ years of experience to join our fraud analytics and AI team! This role combines deep healthcare domain expertise with advanced analytics to detect fraudulent claims or members or providers while ensuring legitimate claims are processed efficiently. You'll work at the intersection of healthcare insurance and data science to predict fraud based on claims and health insurance data.
Position Responsibilities
Time Series & Longitudinal Health Analytics
- Design early warning systems for claims that deviate from expected utilization patterns
Behavioral Analytics & Sequential Pattern Mining
- Analyze provider billing sequences to identify unusual patterns in care delivery, service combinations, or billing timing
- Develop session-based analysis of claimant interactions with care providers to detect orchestrated fraud schemes
- Build behavioral profiles of legitimate vs. fraudulent claim submission patterns
- Develop anomaly identification systems for provider practice trends and claimant care utilization behaviors
Healthcare Claims Analytics
- Predict improperly billed claims based on FWA pattern detection
- Risk score claims based on claim, PA, provider, member and other datasets
- Build validation systems for medical necessity determinations and benefit eligibility criteria
Member & Provider Risk Scoring
- Develop risk scoring models to detect high risk members and providers
Requirements
- PhD or MS Bioinformatics, Computer Science, Clinical Research, or related quantitative field
- 5-10+ years of experience in healthcare analytics or related field
Technical Skills
- Expert-level proficiency in coding languages such as C, C++, Python, R
- Hands on experience in developing AI/ML models
- Advanced statistical modeling and machine learning expertise
- Experience with unsupervised learning, anomaly detection, and imbalanced classification problems
- Experience with model validation, performance monitoring, and regulatory compliance frameworks
- Experience with time series analysis, survival analysis, and longitudinal data modeling
- Proficiency with graph analytics, sequence mining, network analysis, and behavioral pattern recognition
Domain Expertise
- Knowledge of healthcare delivery systems
- Knowledge of medical coding systems (ICD-10, CPT, HCPCS) and healthcare reimbursement models
- Understanding healthcare fraud typologies and detection methodologies, * Willingness to obtain a Public Trust Clearance
- Are you a Green Card holder or a U.S. Citizen? (mandatory response; will not accept EAD/F1 OPT due to federal government contractual requirements of position)
Education:
- Bachelor's (Required)
Experience:
- Data Science: 10 years (Preferred)
Language:
- English (Required)
Benefits & conditions
- 401(k)
- Health insurance
- Paid time off