Data Science Manager, Liquidity and Funding Management

Application Deadline: 09/04/2026 Address: 100 King Street West Job Family Group: Data Analytics & Reporting The 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 Management Corporate 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.

Treasury teams are strategically focused, have a collaborative nature and possess strong problem-solving skills. 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; and make recommendations to improve the use of financial resources.

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 include Plays 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. Designs and produces regular and ad-hoc reports, and dashboards. 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 innovat