Senior Manager, First Party Fraud Analytics - Onboarding

Bank of Montreal; Toronto; On-site; CAD 105,000 - 215,000; Full time

Benefits offered by this job

Health insurance

Tuition reimbursement

Accident and life insurance

Retirement savings plans

Job summary

BMO is seeking a senior data analytics professional to develop risk-based fraud detection rules and dashboards. You will lead advanced analytics initiatives, leverage machine learning, and collaborate with Fraud Strategy, Investigations, and Operations to prioritize investigations and improve detection across onboarding and post-origination activities.

The role requires hands-on experience with SQL, Python, Power BI, and data platforms, plus strong communication skills to present findings to

Qualifications

• Advanced expertise in fraud analytics, statistical analysis, machine learning, and predictive modeling.
• Strong knowledge of first party fraud risk management and fraud detection methodologies related to lending products.
• Expert understanding of mathematics, statistics, and operations research.
• Experience with machine learning and deep learning techniques.
• Data wrangling, preprocessing, and feature engineering.
• Experience with big data environments and analytical platforms.
• Data visualization and storytelling to communicate findings.
• Model governance, ethics, bias, and responsible AI.

Responsibilities

• Develop risk-based rules to identify first-party fraud behaviors, including misrepresentation and synthetic identities.
• Optimize risk-based rules, triggers, and alerting to detect onboarding and post-origination fraud.
• Generate alerts for onboarding channels and assess score effectiveness via PoC to ingest data into models.
• Develop early warning indicators and monitoring tools to detect emerging fraud patterns.
• Build dashboards with relevant metrics and track performance metrics, loss analysis, and testing.
• Partner with Fraud Strategy, Investigations, and Operations to drive actionable investigations.
• Apply analytics, data mining, and behavioral insights to identify new fraud typologies and translate into rules.
• Design and scale predictive models to improve fraud detection and smarter business decisions.
• Conduct large-scale analysis across diverse data sources to identify trends and threats.

Skills

Fraud analytics

Statistical analysis

Machine learning

Predictive modeling

First party fraud risk

Leadership & business skills

Communication

Ambiguity leadership

Education

Bachelor’s Degree in a relevant field

Tools

SQL

Python

PowerBI

Dataiku

SAS

TransUnion

Equifax

Job description

Application Deadline: 11/15/2026 Address: 100 King Street West Job Family Group: Data Analytics & Reporting

Key Responsibilities

• Develop risk-based rules to identify FPF behaviors, including misrepresentation, synthetic identities, bust-outs, stolen IDs onboarding and post-origination fraud.
• Optimize risk-based rules, triggers, and alerting capabilities to identify first party fraud behaviors.
• Generate alerts for our onboarding channels to track delinquency, account monitoring Assess score effectiveness via Proof of Concept to ingest data into models Work with score vendor (TransUnion, Equifax) and risk engines
• Develop early warning indicators and monitoring tools to detect emerging fraud patterns and portfolio shifts.
• Build dashboards with relevant metrics
• Evaluate rule effectiveness through performance metrics, loss analysis, and ongoing testing.
• Partner with Fraud Strategy, Investigations, and Operations teams to ensure alerting frameworks drive actionable and prioritized investigations.
• Use advanced analytics, data mining, and behavioral insights to identify new first-part fraud typologies and translate insights into actionable rules.
• Apply advanced analytics, machine learning, statistical modeling, and data mining techniques to uncover new fraud risks and behavioral patterns.
• Design and scale predictive models and analytical solutions that improve fraud detection and support smarter business decisions.
• Conduct large-scale analysis across diverse data sources to identify trends, opportunities, and emerging threats.
• Leverage big data tools and modern analytics platforms to enhance fraud monitoring and decisioning capabilities.
• Collaborate with product, risk, technology, and business teams to support strategic decision-making, business planning, and future roadmap development.
• Communicate complex analytical concepts and findings to executive and non-technical audiences in a clear and compelling manner.
• Influence enterprise fraud management strategies through thought leadership, innovation, and data-driven recommendations.
• Build strong partnerships across the organization to drive alignment and achieve business objectives.

Qualifications

• Technical & Analytical Expertise
• Advanced expertise in fraud analytics, statistical analysis, machine learning, and predictive modeling.
• Strong knowledge of first party fraud risk management and fraud detection methodologies, related to lending products.
• Expert-level understanding of: Mathematics, statistics, and operations research
• Machine learning and deep learning techniques
• Data wrangling, preprocessing, and feature engineering
• Big data environments and analytical platforms
• Data visualization and storytelling
• Model governance, ethics, bias, and responsible AI
• Experience developing fraud rules, alerts, and risk monitoring frameworks.
• Proficiency with data and analytics tools such as SQL, Python, PowerBI, Dataiku, or comparable platforms.
• Leadership & Business Skills
• Exceptional analytical, problem-solving, and critical-thinking capabilities.
• Strong verbal and written communication skills with the ability to influence senior stakeholders.
• Proven ability to lead through ambiguity and drive enterprise-wide outcomes.
• Demonstrated success building partnerships across multiple functions and levels of the organization.
• Strong collaboration, relationship management, and stakeholder engagement skills.
• Experience leading and developing high-performing analytics teams.
• Education & Experience
• Bachelor’s Degree in a relevant field
• Typically 7-10+ years of relevant experience in fraud analytics, risk analytics, data science, or a related field, or an equivalent combination of education and experience.
• Prior analytical banking experience is an asset.
• Experience with banking products within a fraud scope and various risk engines with a key focus on onboarding
• Hands on skills with SQL, Power BI, Python, Dataiku, SAS
• Prior experience with score vendors (TransUnion, Equifax)
• Technical leader and thought partner with demonstrated success influencing strategy and driving transformational change.

Salary

Salary: $105,000.00 - $215,000.00 Pay Type: Salaried The above represents BMO Financial Group’s pay range and type. Salaries will vary based on factors such as location, skills, experience, education, and qualifications for the role, and may include a commission structure. Salaries for part-time roles will be pro-rated based on number of hours regularly worked. For commission roles, the salary listed above represents BMO Financial Group’s expected target for the first year in this position. BMO Financial Group’s total compensation package will vary based on the pay type of the position and may include performance-based incentives, discretionary bonuses, as well as other perks and rewards.

• BMO also offers health insurance, tuition reimbursement, accident and life insurance, and retirement savings plans.

To view more details of our benefits, please visit: https://jobs.bmo.com/global/en/Total-Rewards

About Us

At BMO we are driven by a shared Purpose: Boldly Grow the Good in business and life. It calls on us to create lasting, positive change for our customers, our communities and our people. By working together, innovating and pushing boundaries, we transform lives and businesses, and power economic growth around the world. As a member of the BMO team you are valued, respected and heard, and you have more ways to grow and make an impact. We strive to help you make an impact from day one - for yourself and our customers. We’ll support you with the tools and resources you need to reach new milestones, as you help our customers reach theirs.

From in-depth training and coaching, to manager support and network-building opportunities, we’ll help you gain valuable experience, and broaden your skillset. To find out more visit us at https://jobs.bmo.com/ca/en.

BMO is committed to an inclusive, equitable and accessible workplace. By learning from each other’s differences, we gain strength through our people and our perspectives. Accommodations are available on request for candidates taking part in all aspects of the selection process.

BMO is a leading bank driven by a single purpose: to Boldly Grow the Good in business and life. Everywhere we do business, we’re focused on building, investing and transforming how we work to drive performance and continue growing the good.

Who we are We’re proud to be fueling growth and expanding possibilities for individuals, families and businesses. More than 12 million customers count on us for personal and commercial banking, wealth management and investment services. As the 8th largest bank in North America by assets, we provide personal and commercial banking, wealth management and investment services to more than 12 million customers. In Canada, the United States and across the globe, we’ll continue to build, invest and transform to drive performance that serves the good that grows.