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 behaviorDevelop anomaly detection systems to flag unusual claims patterns, provider behaviors, and policyholder activitiesCreate graph-based models to uncover fraud rings, provider networks, and suspicious relationship patternsBuild ensemble models that combine temporal, network, and statistical approaches for comprehensive fraud detectionPerform 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 impactDevelop innovative analytical solutions to address emerging fraud schemes and attack vectorsCreate data-driven business rules and decision frameworks for fraud preventionBuild 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 activitiesApply graph mining techniques to discover new fraud networks and relationship patternsResearch and implement state-of-the-art anomaly detection methods for evolving fraud schemesExperiment with novel approaches including graph neural networks, temporal anomaly detection, and multivariate time series analysisCollaborate with business stakeholders to understand evolving fraud challenges

Collaboration & Communication

Partner with claims, underwriting, and compliance teams to implement analytical solutionsPresent findings and recommendations to senior leadership and cross-functional teamsDocument methodologies, model logic, and analytical processes for regulatory complianceContribute to team knowledge sharing and collaborative problem-solving

Required Qualifications:

 

2-4 years of experience in data science, analytics, or machine learning rolesExperience with fraud detection, risk analytics, or financial crime prevention preferredMaster's 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 learningExpert-level SQL skills and experience with database management systemsHands-on experience with machine learning frameworksProficiency with graph analytical methods and librariesExperience 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 dataAnomaly Detection: Strong background in outlier detection methodologies including statistical approaches, machine learning methods and deep learning techniquesGraph Methods: Proven experience with network analysis, community detection, centrality measures, and graph-based fraud detection. Knowledge of graph neural networks and link prediction algorithmsAdvanced understanding of unsupervised learning, clustering, and dimensionality reduction techniquesStrong foundation in statistical modeling, hypothesis testing, and experimental designUnderstanding 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 analysisTime Series Specialization: Background in fraud trend analysis, seasonal pattern recognition, and temporal anomaly detection in claims dataFamiliarity with claims processing workflows and insurance operationsExperience with real-time scoring systems and production model deployment

When you join our team:

 

We’ll empower you to learn and grow the career you want.  We’ll recognize and support you in a flexible environment where well-being and inclusion are more than just words.  As part of our global team, we’ll 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 https://www.manulife.com/en/about/our-story.html.

Manulife 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 recruitment@manulife.com.

Referenced Salary Location

Boston, Massachusetts

Working Arrangement

Hybrid

Salary range is expected to be between

$70,560.00 USD - $131,040.00 USD

If you are applying for this role outside of the primary location, please contact recruitment@manulife.com 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.)