07/07/2026
Address:
33 Dundas Street West
Data Analytics & Reporting
Manager, Loss Forecasting Models
The Manager, Loss Forecasting Models leads the development, enhancement, and governance of advanced forecasting models for retail credit portfolios. This role is highly technical and strategic, focused on applying statistical, machine learning, and AI methodologies to improve loss forecasting accuracy and business decision-making.
The ideal candidate brings strong experience from leading financial institutions, deep quantitative expertise, and hands-on programming skills, along with the ability to lead model initiatives and collaborate with stakeholders across Canada and the U.S.
Key Responsibilities
Model Development & Innovation
- Lead the design, development, and implementation of loss forecasting models for retail credit portfolios.
- Apply advanced statistical techniques and modern machine learning / AI approaches (e.g., GLMs, gradient boosting, random forests, neural networks) to enhance forecasting accuracy and risk insights.
- Drive innovation by incorporating alternative data, new modeling techniques, and automation into forecasting frameworks.
- Oversee the full model development lifecycle: data extraction, feature engineering, model training, validation, benchmarking, and deployment.
- Ensure models comply with internal governance standards and regulatory expectations (e.g., SR 11‑7, IFRS 9 / CECL where applicable).
Data, Analytics & Programming
- Lead the analysis of large, complex datasets from multiple sources using Python, SAS, and SQL.
- Guide exploratory data analysis to identify trends, macroeconomic drivers, and emerging portfolio risks.
- Promote best practices in coding, model reproducibility, and scalable analytics.
- Implement automation and reusable solutions to streamline forecasting and reporting processes.
Model Monitoring & Performance Management
- Oversee ongoing model monitoring, including PSI, KS, AR, calibration, and back-testing.
- Identify model degradation, data drift, and performance gaps; recommend recalibration or redevelopment strategies.
- Ensure robust monitoring frameworks are in place to support proactive risk management and regulatory compliance.
Stakeholder Engagement & Leadership
- Partner with senior stakeholders across Risk, Finance, Product, Strategy, and Model Risk Management.
- Translate complex modeling outputs into actionable business insights.
- Support model validation and audit processes by providing clear documentation and analytical evidence.
- Mentor junior analysts and provide technical guidance on modeling best practices.
Documentation & Governance
- Ensure comprehensive documentation of all models, including methodology, assumptions, limitations, and performance results.
- Maintain high standards of model transparency, explainability, and regulatory compliance.
- Lead responses to model validation, audit, and regulatory inquiries.
Qualifications
Required
- Master’s degree or higher in a quantitative discipline (Statistics, Mathematics, Economics, Data Science, Engineering, Computer Science, or related field).
- Minimum 5+ years of experience in credit risk modeling, loss forecasting, or quantitative analytics within a bank or financial institution.
- Proven experience developing loss forecasting / credit risk models (e.g., PD, LGD, ECL, stress testing).
- Strong hands-on expertise in Python, SAS, and SQL for data manipulation, modeling, and analysis.
- Solid foundation in statistics, econometrics, and predictive modeling techniques.
- Demonstrated experience applying machine learning and AI methods to improve model performance and forecasting outcomes.
- Experience working with large-scale, complex datasets in banking environments.
- Strong problem-solving skills and attention to detail.
Preferred
- Prior experience at leading financial institutions or exposure to multiple banking environments.
- Knowledge of IFRS 9 / CECL frameworks and macroeconomic scenario modeling.
- Experience with model governance frameworks and regulatory expectations (e.g., SR 11‑7).
- Leadership or mentoring experience in analytics or modeling teams.
Applies mathematical and statistical methods to financial and risk management problems (e.g. internal controls; enterprise-wide stress testing and scenario analysis; capital modelling; valuations). Through quantitative analytical modelling, identifies important factors to consider for financial disaster and recovery plans. Conducts research and creates tools that use data to develop scenario-based planning and implements complex mathematical models to help the business make better financial and financial decisions (e.g. investments, pricing, etc.), drive innovation and minimize the impact of uncertainty.
- Develops pricing and quantitative risk models for an assigned portfolio e.g. fixed income, corporate credit and loans.
- Monitors risk in strategies and portfolios alongside project managers or functional leads.
- Conducts research and develops tools that use data to make better financial decisions; such as: investments, pricing, etc.
- Applies knowledge of risk assessment and controls along with extensive understanding of industry compliance standards and regulations.
- Identifies ways of mitigating potential risks; recommends and implements solutions based on analysis of issues and implications for the business.
- Documents data flow, systems and processes to improve the design, implementation and management of business/group processes.
- Conducts quantitative research in risks across strategies and portfolios.
- 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.
- Take measured risks while protecting the bank by applying our Risk Management Framework in the execution of your role, in line with our Risk Culture and within our approved Risk Appetite, making sound and risk informed decisions that align to business strategy, protect assets, and adhere to applicable policy documents (Frameworks, Policies, Standards, Procedures and Supporting documents), laws and regulations.
Qualifications:
Foundational level of proficiency:
- Regulatory capital and stress testing.
- Compliance and regulation.
- Machine learning.
- Learning Agility.
- Systems Thinking.
Intermediate level of proficiency:
- Model risk management.
- Data visualization.
- Data wrangling.
- Data preprocessing.
- Critical thinking.
- Driving Results.
- Verbal & written communication skills.
- Collaboration & team skills.
- Analytical and problem solving skills.
- Data driven decision making.
Advanced level of proficiency:
- Quantitative financial modeling.
- Computational thinking and programming.
- 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.
$82,800.00 - $154,800.00
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
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.
