John Hancock is seeking a Data Scientist to join their Long Term Care Insurance fraud analytics and AI team to protect policyholders and the company from fraudulent claims by building sophisticated detection systems.
Requirements
- Expert-level proficiency in a coding language such as C, C++, Python, R
- Expert level proficiency in SQL
- Experience with time series analysis, survival analysis, and longitudinal data modeling
- Proficiency with graph analytics, sequence mining, network analysis, and behavioral pattern recognition
- Advanced statistical modeling and machine learning expertise
- Experience with unsupervised learning, anomaly detection, and imbalanced classification problems
- Strong feature engineering capabilities, particularly for temporal and sequential data
Responsibilities
- Develop predictive models analyzing patient health trajectories over multi-year periods to identify statistically improbable recovery patterns or care progression anomalies
- Build longitudinal cohort analysis frameworks to detect unusual claim patterns across similar patient populations
- Build temporal feature engineering pipelines that capture disease progression, treatment response patterns, and care critical issue trends
- Design early warning systems for claims that deviate from expected long-term care utilization patterns
- 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 anomaly identification systems for provider practice trends and claimant care utilization behaviors
Other
- PhD or MS Bioinformatics, Computer Science, Clinical Research, or related quantitative field
- 5+ years of experience in healthcare analytics or related field
- Knowledge of healthcare delivery systems
- Knowledge of medical coding systems (ICD-10, CPT, HCPCS) and healthcare reimbursement models
- Familiarity with long-term care insurance products, benefit structures, and claims processes
