Data Science Manager, Liquidity and Funding Management

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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 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.
• Fosters a culture aligned to BMO purpose, values and strategy and role models BMO values and behaviours in all that they do.
• Ensures alignment between values and behaviour that fosters diversity and inclusion.
• Regularly connects work to BMO’s purpose, sets inspirational goals, defines clear expected outcomes, and ensures clear accountability for follow through.
• Builds interdependent teams that collaborate across functional and operating groups to create the highest value for all stakeholders.
• Attracts, retains, and enables the career development of top talent.
• Improves team performance, recognizes and rewards performance, coaches employees, supports their development, and manages poor performance.
• Focus is primarily on business/group within BMO; may have broader, enterprise-wide focus.
• Provides specialized consulting, analytical and technical support.
• Exercises judgment to identify, diagnose, and solve problems within given rules.
• Works independently and regularly handles non-routine situations.
• Broader work or accountabilities may be assigned as needed.

Qualifications:

Intermediate level of proficiency:

• Mathematics, statistics & operations research.
• Deep learning.
• Machine learning.
• Trust, bias and ethics.
• Creative thinking.
• Critical thinking.

Advanced level of proficiency:

• Big data.
• Data visualization.
• Computational thinking and programming.
• Data wrangling.
• Data preprocessing.
• Creative reasoning.
• Verbal & written communication skills.
• Collaboration & team skills.
• Analytical and problem solving skills.
• Influence skills.
• 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 tool sets including but not limited to Spotfire, Tableau, SQL, SAS, R, Python, MATLAB, SPSS, Spark.

Salary:

Pay Type:

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. To request accommodation, please contact your recruiter.

Note to Recruiters: BMO does not accept unsolicited resumes from any source other than directly from a candidate. Any unsolicited resumes sent to BMO, directly or indirectly, will be considered BMO property. BMO will not pay a fee for any placement resulting from the receipt of an unsolicited resume. A recruiting agency must first have a valid, written and fully executed agency agreement contract for service to submit resumes.