Associate Data Scientist - Fraud Analytics
Associate Data Scientist - Fraud Analytics
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Job Description
We are seeking a highly analytical and creative Associate Data Scientist to join our Advanced Analytics and AI team focused on fraud detection and risk mitigation within our long term care insurance business. This role offers the opportunity to develop cutting-edge models and innovative solutions that directly protect our organization and policyholders from fraudulent activities.
Position Responsibilities:
Model Development & Analytics
- Design and build sophisticated fraud detection models with emphasis on time series analysis to identify temporal patterns and trends in fraudulent behavior
- Develop anomaly detection systems to flag unusual claims patterns provider behaviors and policyholder activities
- Create graph-based models to uncover fraud rings provider networks and suspicious relationship patterns
- Build ensemble models that combine temporal network and statistical approaches for comprehensive fraud detection
- Perform advanced statistical analysis on large complex datasets to uncover fraud indicators
Digital Controls & Innovation
- Design and implement digital controls and automated workflows to mitigate fraud impact
- Develop innovative analytical solutions to address emerging fraud schemes and attack vectors
- Create data-driven business rules and decision frameworks for fraud prevention
- Build monitoring systems and dashboards to track model performance and fraud trends
Research & Continuous Improvement
- Conduct time series analysis to identify seasonal fraud patterns emerging trends and change points in fraudulent activities
- Apply graph mining techniques to discover new fraud networks and relationship patterns
- Research and implement state-of-the-art anomaly detection methods for evolving fraud schemes
- Experiment with novel approaches including graph neural networks temporal anomaly detection and multivariate time series analysis
- Collaborate with business stakeholders to understand evolving fraud challenges
Collaboration & Communication
- Partner with claims underwriting and compliance teams to implement analytical solutions
- Present findings and recommendations to senior leadership and cross-functional teams
- Document methodologies model logic and analytical processes for regulatory compliance
- Contribute to team knowledge sharing and collaborative problem-solving
Required Qualifications:
- 2-4 years of experience in data science analytics or machine learning roles
- Experience with fraud detection risk analytics or financial crime prevention preferred
- Masters degree in Statistics Mathematics Physics Engineering Computer Science or other quantitative science discipline
Technical Skills
- Advanced proficiency in Python or R for statistical analysis and machine learning
- Expert-level SQL skills and experience with database management systems
- Hands-on experience with machine learning frameworks
- Proficiency with graph analytical methods and libraries
- Experience with time series methods and libraries
Analytical Capabilities - Core Requirements
- Time Series Analysis: Demonstrated expertise in time series forecasting trend analysis seasonality detection and change point detection. Experience with ARIMA state space models and modern deep learning approaches for temporal data
- Anomaly Detection: Strong background in outlier detection methodologies including statistical approaches machine learning methods and deep learning techniques
- Graph Methods: Proven experience with network analysis community detection centrality measures and graph-based fraud detection. Knowledge of graph neural networks and link prediction algorithms
- Advanced understanding of unsupervised learning clustering and dimensionality reduction techniques
- Strong foundation in statistical modeling hypothesis testing and experimental design
- Understanding of model validation performance metrics and bias detection
Preferred Qualifications
- Advanced Graph Analytics: Experience implementing graph-based fraud rings detection money laundering networks and provider relationship analysis
- Time Series Specialization: Background in fraud trend analysis seasonal pattern recognition and temporal anomaly detection in claims data
- Familiarity with claims processing workflows and insurance operations
- Experience with real-time scoring systems and production model deployment
When you join our team:
- Well empower you to learn and grow the career you want.
- Well recognize and support you in a flexible environment where well-being and inclusion are more than just words.
- As part of our global team well support you in shaping the future you want to see.
#LI-Hybrid
About Manulife and John Hancock
Manulife Financial Corporation is a leading international financial services provider helping people make their decisions easier and lives better. To learn more about us visit is an Equal Opportunity Employer
At Manulife/John Hancock we embrace our diversity. We strive to attract develop and retain a workforce that is as diverse as the customers we serve and to foster an inclusive work environment that embraces the strength of cultures and individuals. We are committed to fair recruitment retention advancement and compensation and we administer all of our practices and programs without discrimination on the basis of race ancestry place of origin colour ethnic origin citizenship religion or religious beliefs creed sex (including pregnancy and pregnancy-related conditions) sexual orientation genetic characteristics veteran status gender identity gender expression age marital status family status disability or any other ground protected by applicable law.
It is our priority to remove barriers to provide equal access to employment. A Human Resources representative will work with applicants who request a reasonable accommodation during the application process. All information shared during the accommodation request process will be stored and used in a manner that is consistent with applicable laws and Manulife/John Hancock policies. To request a reasonable accommodation in the application process contact .
Referenced Salary Location
Boston MassachusettsWorking Arrangement
Salary range is expected to be between
$70560.00 USD - $131040.00 USDIf you are applying for this role outside of the primary location please contact for the salary range for your location. The actual salary will vary depending on local market conditions geography and relevant job-related factors such as knowledge skills qualifications experience and education/training. Employees also have the opportunity to participate in incentive programs and earn incentive compensation tied to business and individual performance.
Manulife/John Hancock offers eligible employees a wide array of customizable benefits including health dental mental health vision short- and long-term disability life and AD&D insurance coverage adoption/surrogacy and wellness benefits and employee/family assistance plans. We also offer eligible employees various retirement savings plans (including pension/401(k) savings plans and a global share ownership plan with employer matching contributions) and financial education and counseling resources. Our generous paid time off program in the U.S. includes up to 11 paid holidays 3 personal days 150 hours of vacation and 40 hours of sick time (or more where required by law) each year and we offer the full range of statutory leaves of absence.
Know Your Rights I Family & Medical Leave I Employee Polygraph Protection I Right to Work I E-Verify I Pay Transparency
Company: John Hancock Life Insurance Company (U.S.A.)Required Experience:
IC
Employment Type
Full-Time
