Application Deadline:09/04/2026Address:100 King Street WestJob Family Group:Data Analytics & ReportingThe Data Science Manager, Liquidity & Funding Management role is an excellent opportunity for a technically strong risk modeling professional to apply advanced statistical and quantitative methods to one of banking’s most strategic and evolving disciplines.Focused on liquidity modeling, stress testing, and balance sheet risk management, this position leads the development of predictive models that help the bank understand how customers, products, and funding sources behave under stressed market conditions. Ideal candidates may come from liquidity risk, credit risk modeling, model validation, stress testing, insurance, pensions, or consulting backgrounds and possess strong Python and SQL skills, with AWS and SageMaker experience as an asset.This role offers exposure to enterprise-wide decision-making and funding strategy, making it a compelling next step for senior analysts or emerging leaders seeking broader business impact beyond traditional credit risk.Data Science Manager Corporate Treasury Liquidity and Funding ManagementCorporate Treasury finds the best ways for BMO to deploy its financial resources within regulatory guidelines and the Enterprise’s risk appetite. The Treasury function plays a key role in the management of the bank’s liquidity, funding, capital, and allocation of financial resources to align with the bank’s overall strategy and to ensure the bank is resilient in its ability to carry out its activities.

Liquidity and Funding Management within Corporate Treasury leverages big data platforms to measure, analyze and oversee the Bank’s internal and regulatory liquidity and funding risks that arise from global business activities; Data Science Manager in Liquidity and Funding Management plays a critical role to promote data driven decision making while collaborating with liquidity risk experts and business partners to leverage BMO’s enterprise database and create insightful funding and liquidity analytics and reports.The candidate is part of a team that is accountable for the quantitative measurement and analysis of the bank’s liquidity and funding risks that arise from global business activities through the development of quantitative and stress testing models. This involves utilizing the latest modeling methodologies and applying those methodologies to build robust risk models to support Corporate Treasury’s liquidity risk framework and business decisions.Key responsibilities and requirements includePlays an active role in the futuristic display of data, and advancement of innovative data strategies to understand consumer trends and address business problems.Leads/participates in the design, implementation and management of new analytics & reporting solutions.Designs, develops, and implements calculators and models for liquidity risk measures with innovative analytical solutions.Structures and assembles data into multi-dimensions with various granularities (e.g., customers, products, transactions, financial instruments).Monitors and tracks tool performance, user acceptance testing, and addresses any issues.Uses data mining and extracting usable data from valuable data sources to assess feasibility of AI/ML solutions for improve 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 cutting-edge 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.Ensures alignment between values and behaviour that fosters diversity and inclusion.Improves team performance, recognizes and rewards performance,



coaches employees, supports their development, and manages poor performance.Provides specialized consulting, analytical and technical support.Machine learning.Creative thinking.Big data.Data visualization.Computational thinking and programming.Data wrangling.Data preprocessing.Creative reasoning.Data driven decision making.Typically between 5 - 7 years of relevant experience and post-secondary degree in related field of study or an equivalent combination of education and experience.Deep knowledge and technical proficiency gained through extensive education and business experience with statistical toolsets including but not limited to Spotfire, Tableau, SQL, SAS, R, Python, MATLAB, SPSS, Spark.Salaries for part-time roles will be pro-rated based on number of hours regularly worked.

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. It calls on us to create lasting, positive change for our customers, our communities and our people.

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.Accommodations are available on request for candidates taking part in all aspects of the selection process.

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📌 Data Science Manager (W/M) (Toronto)
🏢 Bank of Montreal
📍 Toronto