Analyst, Decision Science

Address:

The Analyst, Risk Modeling, supports the development, enhancement, and monitoring of statistical models used across retail credit portfolios. This role is ideal for a new graduate or early‑career quantitative professional who enjoys hands‑on data work and has a strong foundation in statistics and programming.

You will work alongside experienced modelers to build datasets, perform exploratory analysis, run statistical models, and produce high‑quality documentation. This role provides an excellent entry point into credit risk modeling with exposure to both Canadian and U.S. portfolios.

Key Responsibilities

Data & Programming (Major Component)

• Extract, clean, and manipulate large datasets using SAS, Python, and SQL.

• Build datasets used for model development, monitoring, and analysis.

• Conduct exploratory data analysis (EDA) to understand data patterns, anomalies, and risk drivers.

• Automate repetitive analytical processes using efficient, reusable code.

Model Development Support

• Assist in the development of predictive models (e.g., credit risk, PD models, behavioral models) under the guidance of senior team members.

• Perform variable analysis, binning, correlation checks, and model diagnostics.

• Run logistic regression or other statistical techniques as part of model development.

Documentation & Governance

• Draft clear model documentation, technical notes, and data summaries.

• Support preparation for model validation, audit, and governance reviews.

• Ensure work follows internal model risk policies and reproducibility standards.

Model Monitoring

• Help produce model monitoring packages (e.g., PSI, KS, AR, stability checks).

• Investigate data or performance issues and assist in troubleshooting.

Qualifications

Required

• Master’s degree in a STEM field (Statistics, Mathematics, Economics, Engineering, Data Science, Computer Science, or related).

• 0–1 year of experience in a quantitative role (full‑time, co‑op, internship, or research experience all acceptable).

• Strong programming ability in SAS, Python, and SQL.

• Solid understanding of statistics and predictive modeling concepts (e.g., regression, distributions, probability).

• Comfort working with large datasets and strong attention to detail.

• Ability to document analytical work clearly and communicate findings effectively.

If you’re looking for your next dream job, consider this one in BMO’s Enterprise Risk Group where every colleague helps protect and grow the bank by providing independent review and oversight of enterprise-wide risks, working together to maintain a risk management framework and fostering a strong risk culture.  #ERPMDreamJobs

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.

• Exercises judgment to identify, diagnose, and solve problems within given rules.

• Works independently on a range of complex tasks, which may include unique situations.

• Broader work or accountabilities may be assigned as needed.

Qualifications:

Foundational level of proficiency:

• Regulatory capital and stress testing.

• Compliance and regulation.

• Machine learning.

• Learning Agility.

• Systems Thinking.

• Model risk management.

• Data visualization.

• Data wrangling.

• Data preprocessing.

• Critical thinking.

• Driving Results.

Intermediate level of proficiency:

• Quantitative financial modeling.

• Computational thinking and programming.

• Verbal & written communication skills.

• Collaboration & team skills.

• Analytical and problem solving skills.

• Data driven decision making.

• Typically between 4 - 6 years of relevant experience and post-secondary degree in related field of study or an equivalent combination of education and experience.

• Technical proficiency gained through education and/or business experience.

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.