Data scientist

1 month ago

Old Toronto, Canada Société Financière Manuvie Full time

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 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 we are looking for

  • Bachelor's, 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?

  • A competitive salary and benefits packages.
  • A growth trajectory that extends upward and outward, encouraging you to follow your passions and learn new skills.
  • A focus on growing your career path with us.
  • Flexible work policies and strong work-life balance.
  • Professional development and leadership opportunities.

Our commitment to you

  • Values-first culture: We lead with our Values every day and bring them to life together.
  • Boundless opportunity: We create opportunities to learn and grow at every stage of your career.
  • Continuous innovation: We invite you to help redefine the future of financial services.
  • Delivering the promise of Diversity, Equity and Inclusion: We foster an inclusive workplace where everyone thrives.
  • Championing Corporate Citizenship: We build a business that benefits all partners and has a positive social and environmental impact.
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