Lead Data Scientist, Fraud Applied AI & Innovation

RBC • Toronto, ON

3d • Onsite

About The Position

You will lead Fraud Management (FM) Machine Learning (ML) and Artificial Intelligence (AI) advancements, manage and mentor a team of senior data scientists, 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. As a people leader, you will be responsible for the professional development, performance management, and career growth of your team members. 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.

Requirements

• 5+ years of experience in Machine Learning, data mining and statistics
• 1-3 years of people management or team leadership experience
• 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
• Demonstrated ability to mentor, coach and develop junior team members
• Strong interpersonal skills with ability to provide constructive feedback and manage performance
• 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 Haves

• Graduate degree in a quantitative discipline
• Experience managing data scientists or analytics professionals
• Track record of building high-performing teams and developing talent pipelines
• Experience with Docker and Kubernetes
• Experience with Cloud technologies (Azure, AWS, OpenShift)
• Prior experience in fraud detection and data analytics

Responsibilities

• Manage, mentor and develop senior data scientists, providing technical guidance, career coaching and performance feedback
• Conduct regular 1-on-1s, performance reviews, goal setting and development planning for direct reports
• Assign projects, manage workload distribution and ensure team members have opportunities for growth and skill development
• Foster a collaborative team culture, promote knowledge sharing and support the professional growth of team members
• 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

Benefits

• A comprehensive Total Rewards Program
• Leaders who support your development
• Opportunity to build and lead a high-performing team while advancing your leadership career
• Ability to make a difference and lasting impact
• Opportunity to take on progressively greater accountabilities

What This Job Offers

• Job Type: Full-time
• Career Level: Senior