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Data Scientist - Health Fraud Analytics

Manulife

$87,990 - $163,410
Oct 17, 2025
Boston, MA, US
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John Hancock is seeking a Data Scientist to combat fraud in Long Term Care Insurance by developing advanced analytics and AI-driven detection systems, protecting policyholders and the company while ensuring efficient processing of legitimate claims.

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 behavioral profiles of legitimate vs. fraudulent claim submission patterns

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