Royal Bank of Canada

Senior Data Scientist, Fraud Applied AI and Innovation

Royal Bank of Canada Toronto, Ontario, Canada

Financial Services · 10,001+ employees

20 h ago
data-scientist Mid (2-5 yrs) Full-time Canada
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About the role

Develop and deploy machine learning models to improve real-time and batch fraud detection capabilities. Collaborate with stakeholders to design automated data pipelines and provide thought leadership on analytical processes.

What they look for

Machine Learning Python SQL Fraud Detection Data Mining Statistics Predictive Analytics Big Data Git Data Exploration Model Development Automation Risk Analytics Analytical Methodologies Stakeholder Management

Requirements

Requires at least 2 years of experience in machine learning, data mining, and statistics, preferably within fraud or risk analytics. Proficiency in Python, SQL, and big data platforms is essential, along with a degree in a quantitative discipline.

Benefits

Comprehensive Total Rewards Program Professional development support Inclusive workplace

Full description

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:TORONTOCity:

TorontoCountry:

CanadaWork hours/week:

37.5Employment Type:

Full timePlatform:

PERSONAL & COMMERCIAL BANKINGJob Type:

RegularPay Type:

SalariedPosted Date:

2026-08-13Application Deadline:

2026-08-28Note: 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.

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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.

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