Senior Data Scientist, Fraud Detection & Optimization

RBC•Toronto, ON

2d•Onsite

About The Position

As a Senior Data Scientist, Fraud Detection & Optimization, you will be responsible for the development and execution of commercial payment fraud detection strategies using advanced analytical methodologies and techniques. These fraud detection strategies will be applied with the goal of reducing 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.

Requirements

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 (eg: R, SQL, Python etc.)
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 Haves

Experience with Hadoop, Hive, Spark, Scala or other big-data platform technology/tools
Knowledge of Canadian banking and payment industry payments transaction data and financial fraud

Responsibilities

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 process 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 strategies, 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