Director, Card Fraud Strategy and Analytics

Application Deadline:

07/30/2024

Address:

100 King Street West

Job Family Group:

Data Analytics & Reporting

The Financial Crimes Unit (FCU) brings together our Cybersecurity, Fraud, Physical Security and Resilience Planning capabilities to address the ever-growing and increasingly complex global security environment. It is a highly collaborative effort that greatly enhances BMO’s ability to rapidly prevent, detect, respond to, and recover from all security & crisis threats. This position offers a unique experience to learn from experienced leaders in the industry, join a team building the 21st century model for security and helping grow the good by protecting our customers and communities.

• Hybrid role

BMO seeks a qualified and motivated Director, Card Fraud Strategy and Analytics. The Card Fraud Strategy and Analytics Director is responsible for developing and managing the credit card and debit card fraud strategies and analytics for the Canadian and US portfolios.  The Director manages a team of card data scientists and fraud analysts that use various quantitative disciplines to develop, implement, and measure the ongoing effectiveness of card prevention strategies and fraud containment models to achieve the optimal balance of limiting fraud risks and maximizing business growth, alert efficiency and profitability.  This team implements auto-decisioning rules, alert management best practices and fraud intervention policies, balances results with customer experience targets, applies data mining and statistical modeling techniques to isolate new emerging fraud risk to minimize the Banks exposure to serious financial loss and potentially irreparable damage in the market with investors and regulators. 

The Director partners with Global Card Fraud, Card Operations, Banking Fraud Analytics, Technology, Financial Crimes teams, Card Third Party Service Providers, and other key stakeholders.  The candidate must demonstrate the ability to balance strategic thinking, robust analytical and data-mining capabilities, along with strong operational execution.  The candidate needs to be a strong and influential leader with a keen focus on employee development and a proven ability for building and leading large talented teams located across various geographic locations. The individual needs to display excellent communication skills, an ability to influence leaders and peers, and exhibit energy, curiosity, and ability to frame intelligent questions to uncover issues and spearhead the formulation of approach and methodology.

• Plays an active role in the futuristic display of data, and advancement of innovative data strategies to understand consumer trends and address business problems.
• Uses data mining and extracting usable data from valuable data sources to assess feasibility of AI/ML solutions for improved processing and usage of organization data.
• Conducts large-scale analysis of information to discover patterns and trends by combining different modules and algorithms.
• Uses analysis to provide recommendations and advice for business leaders to maintain to maintain market competitiveness.
• Develops prediction systems and machine learning algorithms. Investigates additional technologies and tools for developing innovative data solutions for business stakeholders.
• Collaborate together with the product team and partners to understand and provide data-driven decision making, business planning and future roadmap.
• Operates at a group/enterprise-wide level and serves as a senior specialist resource across BMO.
• Influences how teams/groups work together.
• Applies expertise and thinks creatively to address unique or ambiguous situations and to find solutions to multiple, interdependent, complex problems.
• Communicates abstract concepts in simple terms.
• Fosters strong internal and external networks and works with and across multiple teams to achieve business objectives.
• Anticipates trends and responds by implementing appropriate changes.
• Broader work or accountabilities may be assigned as needed.

Qualifications:

Expert level of proficiency:

• Mathematics, statistics & operations research.
• Deep learning.
• Machine learning.
• Trust, bias and ethics.
• Creative thinking.
• Critical thinking.
• Big data.
• Data visualization.
• Computational thinking and programming.
• Data wrangling.
• Data preprocessing.
• Creative reasoning.
• Verbal & written communication skills.
• Analytical and problem solving skills.
• Influence skills.
• Collaboration & team skills; with a focus on cross-group collaboration.
• Able to mana