Senior Data Scientist, Fraud Detection & Optimization

What is the opportunity?  As a Senior Data Scientist, Fraud Detection & Optimization, you will be responsible for the development and execution of fraud detection strategies using advanced analytical methodologies and techniques. These strategies will reduce RBC’s fraud risk and losses while maintaining a positive client experience and controlling operating costs. You will innovate and implement novel methodologies to improve detection and efficiency across the team, further automating and streamlining processes.

You will contribute to and support a variety of projects and initiatives across Fraud Management and collaborate with multiple stakeholders at varying levels of seniority.

Job Description  What will you do?
Implement advanced analytical methodologies and proactively identify opportunities to innovate new techniques for fraud detection strategy creation and process and technology improvements.
Collaborate with Data Science & Innovation on machine learning and artificial intelligence projects that impact fraud detection, document methodology, and standardize processes to ensure repeatability.
Develop, maintain and optimize fraud detection strategies for non‑traditional channels & products, and explore multiple data sources to proactively identify emerging fraud trends and patterns.
Leverage reporting to monitor the performance of existing fraud detection strategies, optimize these strategies and use analytical tools to improve detection, enhancing the tools & techniques.
Prioritize fraud detection alerts across detection platforms, verify that all rule deployments are accurate and ensure a balance between fraud losses, client experience and operational costs.
Contribute to Fraud Management projects and initiatives, provide detection recommendations and implement detection strategies by project deadlines.
Develop fraud detection analytics best practices, contribute to the development and implementation of the rule strategy framework and create programming code standards for fraud detection.
Collaborate across the team to ensure best practices are applied, act as a technical resource for other team members and respond to inquiries regarding fraud data and detection strategies.
What do you need to succeed?  Must‑have   3+ years’ experience in analytics or data science related roles, working with large, real‑world datasets.
Strong practical knowledge of, and proven experience with, analytical software packages and various programming languages (e.g., R, SQL, Python).
Strong critical thinking and analytical skills with the ability to solve complex problems and develop data‑driven solutions.
Exceptional communication and presentation skills, including the ability to effectively communicate analytical recommendations to technical and non‑technical audiences.
Thought leadership capability to lead complex initiatives and discussions driven by analytical and business insights.
Ability to see the big picture and guide groups with strategic thinking.
Excellent time management skills and demonstrated ability to prioritize workload effectively.
Degree in mathematics, statistics, computer science or related quantitative discipline.
Nice‑to‑have   

Experience with Hadoop, Hive, Spark, Scala or other big‑data platform technology/tools.
Knowledge of Canadian banking and payment industry payment transaction data and financial fraud.
What’s in it for you?
Continued career advancement opportunities.
Exposure to strong mentorship and leadership examples.
A comprehensive Total Rewards Program including bonuses and flexible benefits.
Ability to make a difference and lasting impact.
Work in a dynamic, collaborative, and high‑performing team.

Job Skills  Critical Thinking, Data Administration, Data Mining, Data Modeling, Data Movement, Detail‑Oriented, Group Problem Solving, Quantitative Research, Research Documents.
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: 2026‑02‑18
Final date to receive applications: 2026‑02‑27
Note  Applications will be…