Lead Data Scientist, Fraud Data Science & Innovation

Royal Bank of Canada

  • Toronto, ON
  • Permanent
  • Full-time
  • 7 days ago
Job DescriptionWhat's the opportunity?You will lead Fraud Management(FM) Machine Learning(ML) and Artificial Intelligence(AI) advancements, develop strategy for predictive fraud detection ML models and explore ML/AI technique application. You will set standards for ML model development, ensuring consistency, accuracy and repeatability, collaborate with partners and work with Fraud Strategy, Fraud IT and Enterprise Model Risk Management(EMRM) on emerging fraud risks, solution design and model validation frameworks. You will fully comprehend the technical architecture supporting the Fraud decisioning ecosystem and how it supports DSA detection requirements. As a Subject Matter Expert (SME) on FM initiatives, you will collaborate with stakeholders at varying levels of seniority.What will you do?
  • Lead the development and implementation of the Data Science Machine Learning (ML) strategy and act as key point of contact for all ML models
  • Develop supervised fraud detection models and explore opportunities for unsupervised/anomaly detection applications
  • Plan timelines, resource allocation, standards and best practices for ML model development with DS&I and be responsible for technical validation exercises for new model deployments
  • Collaborate effectively with partners in Fraud IT on continuous improvement of the fraud detection ecosystem, understanding the technical requirements and their impact on the business users in DSA
  • Work with EMRM to enable efficient model validation and develop a strong relationship with Fraud Strategy partners focused on identifying emerging fraud risks and how the application of ML can minimize these risks
  • Identify opportunities and develop solutions to automate/enhance processes through analytical tools and workflows; and utilize technology tools to build the most effective solution; Python, R, Spark, PySpark, etc.
  • Provide thought leadership to support Fraud Management’s key priorities where there is a dependence on data analytics, machine learning or data engineering
  • Leverage expertise with ML and programming to provide support to the rest of the DSA team as required
What you need to succeedMust have:
  • 5+ years of experience in Machine Learning, data mining and statistics
  • Strong practical knowledge of, and proven experience with, analytical software packages and programming languages: Python, R, SQL, etc.
  • Working knowledge of Big Data Framework (Hadoop, etc.)
  • Strong understanding of version control (Git/GitHub)
  • Strong problem solving, research and quantitative skills
  • Exceptional time management and organizational skills, ability to manage multiple projects simultaneously and prioritize workload effectively
  • Proven ability to perform complex data analysis on large volumes of data
  • Professional oral and written communication and presentation skills, including the ability to effectively communicate analytical recommendations to both technical and non-technical audiences.
  • Knowledge of Canadian banking and payment industry, payments transaction data and financial fraud
  • Bachelor’s degree in a quantitative discipline
Nice to have:
  • Graduate degree in a quantitative discipline
  • Experience with Docker and Kubernetes
  • Experience with Cloud technologies (Azure, AWS, OpenShift)
  • Prior experience in fraud detection and data analytics
What’s in it for you?We thrive on the challenge to be our best, progressive thinking to keep growing, and working together to deliver trusted advice to help our clients thrive and communities prosper. We care about each other, reaching our potential, making a difference to our communities, and achieving success that is mutual.
  • A comprehensive Total Rewards Program
  • Leaders who support your development
  • Ability to make a difference and lasting impact
  • Opportunity to take on progressively greater accountabilities
Job Skills Actuarial Modeling, Big Data Management, Commercial Acumen, Data Mining, Data Science, Decision Making, Machine Learning, Natural Language Processing (NLP), Predictive Analytics, Python (Programming Language)Additional Job DetailsAddress: YORK MILLS CENTRE, 36 YORK MILLS RD:TORONTOCity: TorontoCountry: CanadaWork hours/week: 37.5Employment Type: Full timePlatform: PERSONAL & COMMERCIAL BANKINGJob Type: RegularPay Type: SalariedPosted Date: 2025-08-26Application Deadline: 2025-09-12Note: Applications will be accepted until 11:59 PM on the day prior to the application deadline date aboveInclusion and Equal Opportunity EmploymentAt RBC, we believe an inclusive workplace that has diverse perspectives is core to our continued growth as one of the largest and most successful banks in the world. Maintaining a workplace where our employees feel supported to perform at their best, effectively collaborate, drive innovation, and grow professionally helps to bring our Purpose to life and create value for our clients and communities. RBC strives to deliver this through policies and programs intended to foster a workplace based on respect, belonging and opportunity for all.Join our Talent CommunityStay in-the-know about great career opportunities at RBC. Sign up and get customized info on our latest jobs, career tips and Recruitment events that matter to you.Expand your limits and create a new future together at RBC. Find out how we use our passion and drive to enhance the well-being of our clients and communities at .

Royal Bank of Canada