Manulife
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
Master'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 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 Acerca de Manulife y John Hancock Manulife Financial Corporation es un importante proveedor internacional de servicios financieros que ayuda a las personas a tomar decisiones de una manera ms fcil y a vivir mejor. Para obtener ms informacin acerca de nosotros, visite http://www.manulife.com . Manulife es un empleador que ofrece igualdad de oportunidades En Manulife/John Hancock, valoramos nuestra diversidad. Nos esforzamos por atraer, formar y retener una fuerza laboral tan diversa como los clientes a los que prestamos servicios, y para fomentar un entorno laboral inclusivo en el que se aprovechen las fortalezas de las culturas y las personas. Estamos comprometidos con la equidad en las contrataciones, la retencin de talento, el ascenso y la remuneracin, y administramos todas nuestras prcticas y programas sin discriminacin por motivos de raza, ascendencia, lugar de origen, color, origen tnico, ciudadana, religin o creencias religiosas, credo, sexo (incluyendo el embarazo y las afecciones relacionadas con este), orientacin sexual, caractersticas genticas, condicin de veterano, identidad de gnero, expresin de gnero, edad, estado civil, estatus familiar, discapacidad, o cualquier otro aspecto protegido por la ley vigente. Nuestra prioridad es eliminar las barreras para garantizar la igualdad de acceso al empleo. Un representante de Recursos Humanos trabajar con los solicitantes que requieran una adaptacin razonable durante el proceso de solicitud. Toda la informacin que se haya compartido durante el proceso de solicitud de adaptacin se almacenar y utilizar de manera congruente con las leyes y las polticas de Manulife/John Hancock correspondientes. Para solicitar una adaptacin razonable en el proceso de solicitud, envenos un mensaje a recruitment@manulife.com . Ubicacin principal Boston, Massachusetts Modalidades de Trabajo Hbrido Se prev que el rango salarial est entre $70,560.00 USD - $131,040.00 USD Si se est postulando para este puesto fuera de la ubicacin principal, pngase en contacto con recruitment@manulife.com para conocer el rango salarial de su ubicacin. El salario real variar segn las condiciones locales del mercado, la geografa y los factores relacionados con el trabajo pertinentes, como conocimiento, habilidades, calificaciones, experiencia y educacin/capacitacin. Los empleados tambin tienen la oportunidad de participar en programas de incentivos y obtener una compensacin de incentivos vinculada al desempeo comercial e individual. Manulife/John Hancock ofrece a los empleados aptos una amplia variedad de beneficios personalizables, entre ellos, beneficios de salud, odontolgicos, de salud mental, oftalmolgicos, por discapacidad a corto y a largo plazo, cobertura de seguro de vida y por muerte accidental y desmembramiento, adopcin/subrogacin y bienestar, y planes de asistencia al empleado/familiar. Tambin ofrecemos a los empleados admisibles varios planes de ahorro para la jubilacin (incluidos planes de ahorro 401(k) o de pensiones y un plan mundial de propiedad de acciones con contribuciones equivalentes del empleador) y recursos de asesoramiento y educacin financiera. Nuestro generoso programa de das libres pagos en EE. UU. contempla hasta 11 das festivos, 3 das personales, 150 horas de vacaciones y 40 horas de licencia por enfermedad (o ms cuando lo exija la ley) por ao, y ofrecemos todos los tipos de licencias contempladas por la ley. Conozca sus derechos (https://www.dol.gov/agencies/ofccp/posters) Permiso Familiar y Mdico Ley de Proteccin del Empleado contra el Examen Poligrfico (https://www.dol.gov/sites/dolgov/files/WHD/legacy/files/eppac.pdf) Derecho al Trabajo Verificacin Electrnica (E-
Verify
) Transparencia Salarial (https://www.dol.gov/sites/dolgov/files/ofccp/pdf/pay-transp_%20English_formattedESQA508c.pdf) Company: John Hancock Life Insurance Company (U.S.A.) #J-18808-Ljbffr
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
Master'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 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 Acerca de Manulife y John Hancock Manulife Financial Corporation es un importante proveedor internacional de servicios financieros que ayuda a las personas a tomar decisiones de una manera ms fcil y a vivir mejor. Para obtener ms informacin acerca de nosotros, visite http://www.manulife.com . Manulife es un empleador que ofrece igualdad de oportunidades En Manulife/John Hancock, valoramos nuestra diversidad. Nos esforzamos por atraer, formar y retener una fuerza laboral tan diversa como los clientes a los que prestamos servicios, y para fomentar un entorno laboral inclusivo en el que se aprovechen las fortalezas de las culturas y las personas. Estamos comprometidos con la equidad en las contrataciones, la retencin de talento, el ascenso y la remuneracin, y administramos todas nuestras prcticas y programas sin discriminacin por motivos de raza, ascendencia, lugar de origen, color, origen tnico, ciudadana, religin o creencias religiosas, credo, sexo (incluyendo el embarazo y las afecciones relacionadas con este), orientacin sexual, caractersticas genticas, condicin de veterano, identidad de gnero, expresin de gnero, edad, estado civil, estatus familiar, discapacidad, o cualquier otro aspecto protegido por la ley vigente. Nuestra prioridad es eliminar las barreras para garantizar la igualdad de acceso al empleo. Un representante de Recursos Humanos trabajar con los solicitantes que requieran una adaptacin razonable durante el proceso de solicitud. Toda la informacin que se haya compartido durante el proceso de solicitud de adaptacin se almacenar y utilizar de manera congruente con las leyes y las polticas de Manulife/John Hancock correspondientes. Para solicitar una adaptacin razonable en el proceso de solicitud, envenos un mensaje a recruitment@manulife.com . Ubicacin principal Boston, Massachusetts Modalidades de Trabajo Hbrido Se prev que el rango salarial est entre $70,560.00 USD - $131,040.00 USD Si se est postulando para este puesto fuera de la ubicacin principal, pngase en contacto con recruitment@manulife.com para conocer el rango salarial de su ubicacin. El salario real variar segn las condiciones locales del mercado, la geografa y los factores relacionados con el trabajo pertinentes, como conocimiento, habilidades, calificaciones, experiencia y educacin/capacitacin. Los empleados tambin tienen la oportunidad de participar en programas de incentivos y obtener una compensacin de incentivos vinculada al desempeo comercial e individual. Manulife/John Hancock ofrece a los empleados aptos una amplia variedad de beneficios personalizables, entre ellos, beneficios de salud, odontolgicos, de salud mental, oftalmolgicos, por discapacidad a corto y a largo plazo, cobertura de seguro de vida y por muerte accidental y desmembramiento, adopcin/subrogacin y bienestar, y planes de asistencia al empleado/familiar. Tambin ofrecemos a los empleados admisibles varios planes de ahorro para la jubilacin (incluidos planes de ahorro 401(k) o de pensiones y un plan mundial de propiedad de acciones con contribuciones equivalentes del empleador) y recursos de asesoramiento y educacin financiera. Nuestro generoso programa de das libres pagos en EE. UU. contempla hasta 11 das festivos, 3 das personales, 150 horas de vacaciones y 40 horas de licencia por enfermedad (o ms cuando lo exija la ley) por ao, y ofrecemos todos los tipos de licencias contempladas por la ley. Conozca sus derechos (https://www.dol.gov/agencies/ofccp/posters) Permiso Familiar y Mdico Ley de Proteccin del Empleado contra el Examen Poligrfico (https://www.dol.gov/sites/dolgov/files/WHD/legacy/files/eppac.pdf) Derecho al Trabajo Verificacin Electrnica (E-
Verify
) Transparencia Salarial (https://www.dol.gov/sites/dolgov/files/ofccp/pdf/pay-transp_%20English_formattedESQA508c.pdf) Company: John Hancock Life Insurance Company (U.S.A.) #J-18808-Ljbffr