Data Scientist, Fraud Research and Analytics

3 days ago

Toronto, Ontario, Canada RBC - Royal Bank Full time
About the Role

We are seeking a highly skilled Data Scientist to join our Fraud Research and Analytics team at RBC. As a key member of our team, you will be responsible for developing and optimizing fraud detection strategies to maximize operational effectiveness and minimize client impact.

Key Responsibilities
  • Identify patterns, trends, and hidden causation and correlation relationships from Fraud data and advise FM SMT of emerging trends, specific gaps, or systemic issues that impact the Fraud Risk of RBC.
  • Collaborate with appropriate partners for action, correction, awareness, and training.
  • Forecast Financials and Fraud KPI's using predictive analytics techniques and generate insights for executive decision-making and communicating results through insightful visualizations, white papers, reports, and presentations.
  • Research business problems, develop solutions to support investigation and analysis, and lead progression of analytics methodology, tools, and measurement to create development templates for automation.
  • Build the foundation of information in consolidated data repositories for Operations, Fraud Events, Fraud Performance, and Financials.
  • Provide a complete picture of the fraud landscape with drill-down capabilities for root cause analysis and deliver self-serve interactive visualizations through accessible platforms like Tableau.
  • Conduct Code Reviews and develop standards for Development practices and partner with project teams to support information required for analysis of the current state.
  • Deliver Project Reporting for Fraud Events, Performance, Operational, and Financial KPI's and KRI's and Program Benefits measurements to track success criteria of the Project Business Case.
Requirements
  • 2+ years' experience in a Data science and analytics.
  • Advanced capability in using Python, R, PySpark, SAS, SQL, and Tableau.
  • Experience with Databases and Data Structures (RDBMS, Hadoop, etc.).
  • Ability to apply data and analytics concepts to business problems and explain business value of data and analytics concepts.
  • Ability to multi-task and prioritize and complete projects effectively and in a timely manner.
  • Strong team player with a track record of collaboration and experience working as part of an agile team.
  • Professional verbal and written communication and presentation skills, and ability to provide consultation, analysis, and recommendations on a broad range of projects in a deadline-driven environment with ambiguity.
Preferred Qualifications
  • Good understanding of Canadian Financial Institutions, with a focus on Fraud/Risk Operations.
  • Degree in mathematics, statistics, economics, computer science, software engineering, or related quantitative field.
What We Offer
  • Fair compensation.
  • Challenging work in a fast-paced timeline-driven work environment.
  • Ability to make a difference and lasting impact.
  • Work with a great and supportive team.

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