Risk Analytics Manager

3 weeks ago


Toronto, Ontario, Canada Scotiabank Full time
About the Role

This is a pivotal position within Scotiabank's Global Risk Management team, where you will play a key role in accelerating benefits for customers and the bank. As a Manager of Risk Analytics, you will leverage enterprise-level data management tools and advanced analytics to collaborate closely with Global Risk teams, business lines, Digital Banking, and IT.

Key Responsibilities
  • Develop and Implement Innovative Credit Solutions: Utilize advanced and predictive data analytics, big data, and AI/machine learning techniques to research, develop, and implement innovative credit solutions using growth and strategy optimization opportunities in Caribbean and Central American markets.
  • Lead Strategy Design Thinking: Collaborate with business partners, subject matter experts, and external consultants to lead strategy design thinking, enhancing risk-reward predictions, customer segmentation, credit limits, risk-based pricing, and fraud detection across the full credit lifecycle.
  • Utilize Agile Framework: Prioritize and deploy data science projects, aligning with project scope and timelines, utilizing the Agile framework.
  • Collaborate with Business Partners: Collaborate with Toronto and local business partners to implement new credit solutions in selected markets, monitoring key performance indicators for scalable deployment in an agile and rapid environment.
  • Partner with Analytics Areas: Partner with other analytics areas to assist use case development and deployment.
  • Define Data Engineering Requirements: Define data engineering, visualization, and machine learning requirements in collaboration with the Business Intelligence team and key stakeholders.
  • Contribute to Team Standards: Actively contribute to developing and maintaining team standards, tools, and best practices.
Requirements
  • University Degree: University degree in a relevant STEM discipline (Science, Technology, Engineering, and Mathematics).
  • Data Analysis Skills: Ability to work with large volumes of structured and unstructured non-traditional data.
  • Programming Skills: Proficiency in big data tools and programming languages (e.g., SAS, SQL, Spark).
  • Machine Learning Experience: Experience with machine learning and other AI techniques for strategy design.
  • Collaboration Skills: Strong collaboration skills to translate technical knowledge into business value.
  • Communication Skills: Effective communication skills for project documentation and presentations.
  • Social Skills: Excellent social skills to navigate team dynamics.


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