Senior Data Scientist, Fraud Applied AI and Innovation

Job summary

Develop and deploy machine learning models to improve fraud detection capabilities and optimize productivity tools. Collaborate with stakeholders to design automated workflows and provide thought leadership on data analytics initiatives.

Job details

Job Description What's the opportunity? You will apply machine learning, artificial intelligence and advanced analytical methodologies to support Fraud Management’s key priorities. Your work will focus on developing predictive models for improving fraud detection capabilities, optimizing existing productivity tools, creating automated workflows to replace manual processes, designing forward thinking and innovative solutions to complex problems, etc. You will represent the Applied AI & Innovation team as a Subject Matter Expert (SME) on projects and initiatives across Credit & Fraud Management (CFM) and collaborate with multiple stakeholders at varying levels of seniority. You will also assist in developing best practices for analytical processes. What will you do? Develop and deploy machine learning models for real-time and batch fraud detection following all model development standards Contribute to the ML strategy for Credit & Fraud Management, integrate models into the detection ecosystem, and continuously monitor and optimize model performance Partner with Detection Analytics and Governance teams to incorporate feedback and communicate changes that impact fraud detection workflows Design and implement automated data pipelines to replace manual fraud review processes, leveraging modern ML frameworks Identify opportunities and develop automated pipelines to replace or enhance existing processes, utilizing the full suite of available technology and tools to build the most effective solution Provide thought leadership on data analytics and machine learning to support fraud management priorities and deliver strategic initiatives Conduct deep data exploration ensuring data quality and governance What you need to succeed Must have: 2+ years of experience in machine learning, data mining, and statistics, ideally applied to fraud detection or risk analytics Strong ability to analyze large datasets and present actionable insights to diverse stakeholders Proficiency in Python, SQL, and ML frameworks. Experience with big data platforms and version control systems (Git) Excellent communication skills with the ability to translate complex analytical findings to both technical and non-technical audiences Strong time management skills and ability to manage multiple projects simultaneously Degree in a quantitative discipline (Computer Science, Statistics, Mathematics, Engineering, or related field) with strong problem-solving skills Nice to have: Knowledge of Canadian banking and payment industry, payments transaction data and financial fraud Experience with containerization and orchestration platforms (Docker, Kubernetes, OpenShift) Prior experience in fraud detection data analytics Experience with model explainability tools and fairness/bias testing in models 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 Big Data Management, Data Science, Decision Making, Machine Learning (ML), Predictive Analytics, Python (Programming Language), Version Control Additional Job Details Address: YORK MILLS CENTRE, 36 YORK MILLS RD:TORONTO City: Toronto Country: Canada Work hours/week: 37.5 Employment Type: Full time Platform: PERSONAL & COMMERCIAL BANKING Job Type: Regular Pay Type: Salaried Posted Date: 2026-09-28 Application Deadline: 2026-10-12 Note: Applications will be accepted until 11:59 PM on the day prior to the application deadline date above Our Employment Opportunities At RBC, we are guided by living shared values of Client First, Integrity, Collaboration, Respect and Excellence and winning together as One 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 Community Stay 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 jobs.rbc.com. RBC is presently inviting candidates to apply for this existing vacancy. Applying to this posting allows you to express your interest in this current career opportunity at RBC. Qualified applicants may be contacted to review their resume in more detail.

What you’ll do

Develop and deploy machine learning models to improve fraud detection capabilities and optimize productivity tools. Collaborate with stakeholders to design automated workflows and provide thought leadership on data analytics initiatives.

Requirements

Requires at least 2 years of experience in machine learning, data mining, and statistics, preferably within fraud or risk analytics. Candidates must possess a degree in a quantitative discipline and proficiency in Python, SQL, and ML frameworks.

Benefits

• Comprehensive Total Rewards Program • Professional development support • Opportunity for impact

Listed skills

• SQL · Preferred
• Machine learning · Preferred
• Git · Preferred
• Python · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Machine Learning
• Data Mining
• Statistics
• Fraud Detection
• Risk Analytics
• Python
• SQL
• ML Frameworks
• Big Data Platforms
• Git
• Data Exploration
• Data Governance
• Predictive Modeling
• Automated Workflows
• Analytical Processes
• Workplace Inclusivity
• Pipelines
• Workflow Management
• Git (Version Control System)
• Advanced Analytics
• Workflow Automation
• Thought Leadership
• Artificial Intelligence
• Data Analysis
• Automation
• Big Data
• Commercial Banking
• Management
• Containerization
• Decision Making
• Version Control
• Communication
• Computer Science
• Data Quality
• Governance
• Innovation
• Problem Solving
• Python (Programming Language)
• Mathematics
• OpenShift
• Predictive Analytics
• Productivity Software
• SQL (Programming Language)
• Time Management
• Transaction Data
• Kubernetes
• Data Pipelines
• Docker (Software)
• Machine Learning Strategy
• Machine Learning Frameworks

Job areas

• Data & Analytics
• Technology
• Finance & Accounting
• Software
• Engineering
• Applied Data Scientist
• Research Scientist
• Physical and Engineering Science Technicians Not Elsewhere Classified
• Physical Scientists, All Other