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Quantitative Modeling Jobs in Toronto, ON (NOW HIRING)

PhD with 3+ years, MS or MA with 6+ years, or BS or BA with 8+ years of data science or quantitative modeling experience * 3+ years in Product Analytics, Experimentation and Causal Inference

New

The role requires strong quantitative skills, programming capability, clear communication, and an ... Model Development: Work on statistical models to project PPNR (Pre-Provision Net Revenue) as a ...

As an Applied Scientist on the team, you will bring deep expertise in quantitative modeling techniques such as Sequential Recommender Systems, Deep Learning, Reinforcement Learning or Hidden Markov ...

As a part of our team, you will bring deep expertise in Generative AI and quantitative modeling (forecasting, recommender systems, reinforcement learning, causal inferencing or generative artificial ...

Experience with geospatial analysis, large datasets, and quantitative model development. * Strong communication, stakeholder management, and project delivery skills. Preferred Qualifications

New

... quantitative modeling techniques such as Sequential Recommender Systems, Deep Learning, Reinforcement Learning or Hidden Markov Models. You have the scientific and technical skills to build and ...

Strong skills in quantitative methods including statistical analysis, and credit risk modeling * Strong skills in quantitative methods and computer technology, such as Python, R and SAS * 3-5 years ...

Showing results 21-40

Quantitative Modeling information

See Toronto, ON salary details

$31.5K

$135.3K

$251.9K

How much do quantitative modeling jobs pay per year?

As of Aug 10, 2026, the average yearly pay for quantitative modeling in Toronto, ON is $135,272.00, according to ZipRecruiter salary data. Most workers in this role earn between $93,525.00 and $167,009.00 per year, depending on experience, location, and employer.

What are typical daily tasks and projects for someone in a quantitative modeling role?

In a Quantitative Modeling position, your daily activities usually include analyzing large datasets, building and validating predictive models, and developing algorithms to solve business or financial problems. You might spend time coding, running simulations, and interpreting model outputs to inform strategy or risk assessment. Collaboration is common—you'll often work with data scientists, business analysts, or subject matter experts to refine models and ensure they're aligned with organizational goals. The work is intellectually stimulating and fast-paced, with opportunities to see your analytical insights directly impact decision-making.

What is a quantitative modeling?

A Quantitative Modeling job involves using mathematical, statistical, and computational techniques to analyze data and construct models that help businesses make informed decisions. Professionals in this field work in finance, risk management, economics, and other industries to develop predictive models, optimize strategies, and assess uncertainties. They often use programming languages like Python, R, or MATLAB, along with machine learning and statistical methods, to solve complex problems.

What are the key skills and qualifications needed to thrive in the quantitative modeling position, and why are they important?

To excel in Quantitative Modeling, a strong foundation in mathematics, statistics, and data analysis is essential, often complemented by a degree in a quantitative field such as mathematics, finance, engineering, or physics. Proficiency in programming languages like Python, R, MATLAB, or statistical software, as well as familiarity with data visualization tools and financial modeling certifications (such as CFA or FRM), is highly valued. Effective quantitative modelers possess strong problem-solving abilities, attention to detail, and the ability to communicate complex findings clearly to both technical and non-technical stakeholders. These skills enable accurate, data-driven decision-making and the creation of robust predictive models in business, finance, or technology sectors.

What are popular job titles related to Quantitative Modeling jobs in Toronto, ON? For Quantitative Modeling jobs in Toronto, ON, the most frequently searched job titles are:
Infographic showing various Quantitative Modeling job openings in Toronto, ON as of August 2026, with employment types broken down into 86% Full Time, 11% Part Time, and 3% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $135,272 per year, or $65 per hour.

Senior Manager, Unsecured Lending Portfolio Management

BMO Capital Markets

Toronto, ON

CA$86K - CA$160K/yr

Full-time

Medical, Life, Retirement

Re-posted 9 days ago


Job description

Application Deadline:

08/02/2026

Address:

33 Dundas Street West

Job Family Group:

Audit, Risk & Compliance

The Senior Manager, Unsecured Lending Portfolio Management plays a critical role in designing and executing advanced credit acquisition and account management strategies across Credit Card and Unsecured Lending portfolios. This position combines strategic thinking with hands-on analytical execution to deliver solutions that drive profitable growth, enhance customer experience, and maintain portfolio resilience within the organization's risk appetite.

Working closely with cross-functional partners in Product, Risk, Technology, Analytics, and Operations, the Senior Manager develops scalable, automated strategies leveraging decision tree technologies, machine learning-enabled models, and optimization tools. This role ensures strategies evolve with customer behavior and market dynamics while adhering to governance and regulatory standards.

Key Responsibilities

  • Strategy Development & Execution
    Design and implement customer-level account management strategies using decision tree and optimization platforms, aligning actions to growth, profitability, and risk objectives.

  • Quantitative modeling & analytics (ML/statistics to decision outcomes):

  • Apply statistical and machine learning techniques to develop models and decision frameworks; run tests, conduct statistical analysis, and interpret results to drive strategy changes.

  • Create simulation/forecasting frameworks to estimate the financial and risk impacts of strategy decisions; compare realized outcomes vs. expectations and embed continuous improvement loops.

  • Model Application & Interpretation
    Act as a key model user, applying models and scores within strategy logic, ensuring proper interpretation and segmentation to differentiate risk across the portfolio.

  • Analytical Insights & Innovation
    Identify opportunities for new segmentation approaches, behavioral scores, and analytical enhancements to improve predictive power and strategy performance.

  • Champion-Challenger Testing
    Execute structured testing frameworks to evaluate and refine treatments, segmentation schemes, and decision pathways.

  • Lifecycle Strategy Support
    Contribute to strategy design for acquisition, credit limit management, exposure optimization, early warning treatments, and performance-based interventions, ensuring alignment across the customer lifecycle.

  • Technology & Deployment Partnership
    Collaborate with Technology and Analytics teams to translate strategy logic into deployable decision rules, ensuring technical feasibility and operational integrity.

  • Portfolio Monitoring & Reporting
    Deliver data-driven insights on portfolio performance and emerging trends; recommend proactive adjustments to maintain performance within risk appetite.

  • Governance & Compliance
    Ensure strategies comply with credit policy, regulatory requirements, and model governance standards, including documentation and monitoring.

Qualifications & Experience

  • 7+ yearsof experience in Credit Card/Personal Unsecured lending products and/or Unsecured Lending acquisition and account management strategy.

  • Graduate degree in a quantitative discipline (Statistics, Mathematics, Actuarial Science, Engineering, Finance, Economics, or related field).

  • Strong understanding of credit risk concepts and practical experience as a model user.

  • Strong understanding of credit lifecycle economics, ROE drivers, and riskreturn optimization principles.

  • Proven expertise in applying machine learning and data science techniques to develop and optimize credit risk strategies, ensuring statistical robustness, stability, and alignment with business objectives

  • Proficiency with decision engines, decision tree software, and analytical platforms (e.g., Python, FICO, SAS, SQL, ML scoring systems) ; ability to translate complex analysis for senior audiences.

  • Demonstrated ability to translate analytical insights into executable strategies.

  • Experience managing cross-functional projects and influencing stakeholders.

  • Familiarity with credit policy, regulatory frameworks, and model governance.

  • Commitment to innovation, experimentation, and continuous improvement.

  • Strong communication, influencing, and stakeholder management skills; able to operate autonomously in a fastpaced environment.

Salary:

$86,000.00 - $160,000.00

Pay Type:

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.