The Opportunity
We are seeking a motivated Data Scientist to join the Canadian Advanced Analytics team. This role is pivotal in developing sophisticated AI and ML models to enhance Manulife’s anti-fraud program. As a Data Scientist, you will help develop and implement robust analytical solutions, applying both traditional and emerging machine learning and AI techniques including but not limited to outlier detection, link analysis, and deploying applications on cloud platforms like Azure. The successful candidate will work closely with multi-functional teams to design and implement fraud detection algorithms, contributing to the security and integrity of our financial services.
Responsibilities
Collaborate with the anti-fraud team to understand requirements and translate business problems into analytical solutions.
Conduct data exploration and preprocessing to identify patterns, trends, and anomalies in transactional data.
Develop and refine machine learning models for fraud detection, applying a variety of data sources and advanced analytical techniques.
Stay abreast of the latest developments in fraud detection technology and analytics methods.
Contribute to the continuous improvement of the anti-fraud program's analytical capabilities.
Develop analytical solutions using ML, graph analytics and link analysis, etc. to support investigations of fraud or misconduct
Design and implement experiments to validate and optimize machine learning models, ensuring accuracy, efficiency, and scalability.
Deploy machine learning models and applications on cloud platforms like Azure ML or Databricks, ensuring seamless integration and scalability.
Collaborate with data engineers and ML engineers to integrate data science solutions into existing systems and workflows.
Communicate complex technical concepts and findings to both technical and non-technical partners, ensuring clear understanding and agreement
What motivates you?
What we are looking for
Bachelor', Master's degree, or Ph.D. in Computer Science, Data Science, Statistics, Engineering, or a related field.
Proven experience in data science, analytics, or a related field, with a focus on fraud detection preferred.
Proficiency in programming languages such as Python and experience with machine learning libraries/frameworks, e.g., PyTorch, scikit-learn, graph databases (Neo4j/Cypher, Cosmos DB/Gremlin).
Knowledge of professional software engineering practices & standard methodologies for the full software development process, including coding standards, code reviews, source control management, build processes, testing, and operations.
Experience with AzureML, Databricks, and PowerBI
Strong collaboration and elaboration skills; demonstrates a strong commitment to organizational success; shares resources and demonstrates knowledge across the organization.
Strong problem-solving skills and the ability to think critically and creatively to develop innovative solutions.
Excellent communication and collaboration skills, with the ability to work effectively in multi-functional teams.
What can we offer you?
Our commitment to you
#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.
Primary Location
Toronto, OntarioWorking Arrangement
HybridSalary range is expected to be between
$74,270.00 CAD - $137,930.00 CADIf 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 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 and a global share ownership plan with employer matching contributions) and financial education and counseling resources. Our generous paid time off program in Canada includes holidays, vacation, personal, and sick days, and we offer the full range of statutory leaves of absence. If you are applying for this role in the U.S., please contact recruitment@manulife.com for more information about U.S.-specific paid time off provisions.
Yearly based
CAN, Ontario, Toronto, 250 Bloor Street East