Data Scientist, Fraud Predictive Analytics

Description

Application Deadline:

11/29/2026

Address:

100 King Street West

Job Family Group:

Data Analytics & Reporting

Hybrid role

Applies knowledge of advanced analytic algorithms and technologies (e.g. machine learning, deep learning, artificial intelligence) to deliver better prediction models and/or intelligent automation that enables smarter business decisions, improved customer experience, and drives productivity. Applies strong communication and story-telling skills to summarize statistical/algorithmic findings, draw business conclusions, and present actionable insight in a way that resonates with business/groups. Drives innovation through the development of Data & AI products that can be leveraged across Financial Crimes Unit to build advanced fraud detection, fraud investigation, fraud prevention tools/models.

Conducts research to identify, assess and recommend viable, practical solutions to specific financial crimes /criminal risk exposures

Develops and maintains an understanding of the financial crime management processes, frameworks and techniques.

Recommends and implements solutions based on analysis of issues and implications for the business.

Understands and analyzes complex business problem, then formulates data-driven hypotheses to drive business value.

Builds effective relationships with internal/external stakeholders and ensures alignment.

Supports data collection, integration, and retention requirements for data.

Defines innovative data solutions to loosely defined business problems by leveraging pattern detection over potentially large datasets.

Diagnoses and resolves predictive / analytical model performance issues while monitoring system performance and implementation of efficiency improvements.

Develops analytical solutions and makes recommendations based on an understanding of the business strategy and stakeholder needs.

Works with various data owners to discover and select available data from internal sources and external vendors (e.g. financial crime data) to fulfill analytical needs.

Applies scripting / programming skills to assemble various types of source data (unstructured, semi-structured, and structured) into well-prepared datasets with multiple levels of granularities (e.g., demographics, customers, products, transactions).

Develops agreed analytical solution by applying suitable statistical & machine learning techniques (e.g., A/B testing, prototype solutions, mathematical models, algorithms, machine learning, deep learning, artificial intelligence) to test, verify, refine hypotheses.

Uses the appropriate algorithms to discover patterns.

Supports development of tools and delivers training for data analytics and AI.

Broader work or accountabilities may be assigned as needed.

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. To request accommodation, please contact your recruiter.

Requirements

• Typically between 5 - 7 years of relevant experience in Data Science & Analytics and post-secondary degree in related field of study or an equivalent combination of education and experience.
• Advanced degree in Computer Science, Mathematics, Physics, Engineering, Statistics, or other quantitative disciplines and/or equivalent experience
• Experience with programming languages (e.g. SQL, Python, PySpark) and machine learning /deep learning algorithms/packages (e.g. XGBoost, H2O, SparkML).
• Deep proficiency in statistical analysis, quantitative analytics, forecasting/predictive analytics, multivariate testing, and optimization algorithms.
• Experience building fraud models (investigation, detection, prevention) for a large Financial Institution

Conditions

$80,000.00 - $175,000.00

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