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Credit Risk Model Validation Jobs in Ontario (NOW HIRING)

Scotiabank

Director Risk Run and Analytics

Toronto, ON · On-site

Partner with Market Risk, CCR (Counterparty Credit Risk), Model Risk, Quants, Infrastructure, and Engineering teams to strengthen the platform and reduce operational risk. * Ensure the platform can ...

Rogers Communications

Sr Analyst Credit Risk

Toronto, ON

... and validating forecasting •     Provide business recommendations based on analyses to ... Miner, SPSS or Model Builder.  A high aptitude for learning new analytical software ...

CIBC

Senior Manager, Credit Risk Solutions

Toronto, ON · Hybrid

... capital models principles (SACCR, IMM, etc), best practices, processes, procedures, trading ... valid work or study permit. * We may ask you to complete an attribute-based assessment and other ...

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All JobsCredit Risk Model Validation JobsCredit Risk Model Validation Jobs in Ontario

Credit Risk Model Validation information

See Ontario salary details

$23K

$110.4K

$199K

How much do credit risk model validation jobs pay per year?

As of Sep 11, 2026, the average yearly pay for credit risk model validation in Ontario is $110,417.00, according to ZipRecruiter salary data. Most workers in this role earn between $71,500.00 and $143,000.00 per year, depending on experience, location, and employer.

What is credit risk model validation?

Credit risk model validation is the process of ensuring that models used to assess the creditworthiness of borrowers are accurate, reliable, and compliant with regulatory standards. This involves independent review and testing of the model's design, data, assumptions, and performance. The goal is to identify any weaknesses or limitations that could affect the model's ability to predict credit risk, reduce financial losses, and maintain regulatory compliance. Model validation is typically performed by specialists who are not involved in the model's development to ensure objectivity.

What are some common challenges faced by professionals in credit risk model validation roles?

Professionals in Credit Risk Model Validation often encounter challenges such as staying up-to-date with evolving regulatory requirements and ensuring models remain compliant. They must also navigate the complexities of validating models that use advanced statistical techniques or machine learning, which requires both technical expertise and a thorough understanding of the underlying business context. Additionally, clear communication with stakeholders—like model developers, auditors, and risk managers—is essential to address findings and recommend improvements effectively. Managing tight deadlines and balancing multiple validation projects simultaneously can also be demanding.

What are the key skills and qualifications needed to thrive in credit risk model validation, and why are they important?

To thrive in Credit Risk Model Validation, you need a strong background in quantitative finance, statistics, and risk management, usually supported by a relevant degree such as in mathematics, finance, or engineering. Familiarity with statistical programming languages (such as Python, R, or SAS), model validation frameworks, and regulatory guidelines like Basel accords is crucial. Attention to detail, critical thinking, and clear communication skills help you effectively analyze models and convey complex findings to stakeholders. These competencies are vital for ensuring accurate risk assessment, regulatory compliance, and the robustness of financial institutions' credit risk models.

What is the difference between Credit Risk Model Validation vs Credit Risk Analyst?

AspectCredit Risk Model ValidationCredit Risk Analyst
Primary FocusAssessing and validating the accuracy of credit risk modelsAnalyzing credit data to assess borrower risk and support lending decisions
Skills & CertificationsStatistical, quantitative skills; certifications like FRM or CFA often preferredFinancial analysis skills; relevant certifications like CFA or credit-specific training
Work EnvironmentQuantitative teams within risk management or model validation unitsCredit departments, lending teams, or risk management units

While both roles involve credit risk, Credit Risk Model Validation focuses on testing and validating models' accuracy, whereas Credit Risk Analysts evaluate individual creditworthiness to inform lending decisions. The validation role is more technical and model-focused, while analysts work directly with credit data and client assessments.

What are popular job titles related to Credit Risk Model Validation jobs in Ontario?

For Credit Risk Model Validation jobs in Ontario, the most frequently searched job titles are:

What job categories do people searching Credit Risk Model Validation jobs in Ontario look for?

The top searched job categories for Credit Risk Model Validation jobs in Ontario are:

Credit Risk Model Validation jobs near you
Infographic showing various Credit Risk Model Validation job openings in Ontario as of September 2026, with employment types broken down into 75% Full Time, and 25% Part Time. Highlights an 100% In-person job distribution, with an average salary of $110,417 per year, or $53.1 per hour.

Manager, Forecasting Models - Retail & Small Business

Toronto, ON • On-site, Remote

Scotiabank
Banking and Credit Intermediation • 10K+ employees
Learn more about Scotiabankexternal

Full-time

Medical, Retirement

Re-posted yesterday

Job description

Requisition ID: 269885 
Join a purpose driven winning team, committed to results, in an inclusive and high-performing culture.

As a Manager, you will report directly to a Senior Manager or Director and be a critical member of a team overseeing a portfolio of forecasting models and analytic processes. You will support - from conception through execution and governance - the regulatory capital (AIRB) models covering all of the Bank's retail and small business product lines. You will collaborate, on a regular basis, with a wide range of stakeholders and internal partners including Provisioning, Model Operations, Finance, Collections, Model Validation and Governance, Technology & Data, Compliance and Audit.

You will have access to both traditional SAS tools and a modern machine learning stack that includes on-premise GPU computing, open source Jupyter development environments, a Hadoop cluster, containerized API model deployment and data visualization business intelligence tools.Under the guidance of your Director, your team of risk modeling experts will use these tools to develop advanced risk prediction and loss estimation forecasting models that will be used to make decisions worth $billions every month and therefore they need to be not only precise and accurate, but highly stable, explainable, compliant, secure and useful. You will be responsible for understanding the goals & priorities set for you, executing them efficiently with a perpetual eye on quality, asking questions often and delivering results in harmony with your teammates.

 

Is this role right for you? In this role, you will:

  • Lead with integrity and are committed to doing the right thing, the right way.
  • Combine intellectual curiosity with practical problem-solving to drive meaningful outcomes.
  • Embrace ambitious goals and take ownership of delivering measurable results.
  • Enjoy collaborating with diverse stakeholders and learning from colleagues across different functions, backgrounds, and technical skillsets.
  • Appreciate the responsibility that comes with developing models that directly influence the Bank's financial and regulatory reporting.
  • Can interpret complex regulatory requirements and identify opportunities to enhance efficiency while maintaining the highest standards of compliance.
  • Possess a strong understanding of credit risk fundamentals, including PD, LGD, EAD, and RWA, and can apply these concepts across a variety of portfolios and products.
  • Have a passion for programming, analytics, data, and predictive modeling, and enjoy solving complex business challenges through quantitative methods.
  • Hold yourself to a high standard of quality, rigor, and governance in both your analytical work and decision-making.
  • Communicate complex concepts clearly and effectively through both written and verbal presentations.
  • Bring energy, professionalism, and a collaborative spirit to everything you do while enjoying the journey along the way.

Do you have the skills that will enable you to succeed in this role? - We'd love to work with you if you have:

  • Bachelor's Degree in Mathematics, Computer Science, Engineering or an equivalent technical field
  • A demonstrated history of analytic problem solving and sound judgment 
  • Experience as an analyst or data scientist with a track record of accomplishments working on cross-functional teams
  • Strong English-language verbal and written communications skills: the ability to distill abstract business requirements into analysis, concisely convey technical outcomes, tell a story visually with data, prepare and edit high-quality documentation and be accepted as a trusted advisor by peers
  • Able to work remotely and on-site on multiple activities simultaneously and meet deadlines.
  • Strong fundamental understanding of statistics
  • 2+ years of overall experience in analytic roles developing and using predictive, risk and/or forecasting models
  • Highly proficient in 1 or more analytical programming languages (Python, R, SAS, etc.), SQL (Teradata, Oracle, DB2, SQL Server) and multiple environments (Unix & Windows)
  • 1 or more years of experience with big data platforms / integration (Hadoop, Spark, Hive, Avro)
  • Knowledge about credit risk models / scorecards

 Skills considered an asset are the following:

  • Proficient reading, writing and speaking Spanish
  • Experience with credit risk forecasting and/or financial reporting frameworks
  • Experience developing credit risk models / scorecards
  • Experience working within loss forecasting, AIRB or IFRS9 frameworks
  • Domain expertise with any retail & small business banking products and/or risk management practices
  • FRM, CFA credentials
  • Experience training and deploying machine learning models using common Python open source frameworks (i.e., scikit-learn) and/or Python DevOps
  • Microsoft Office (Excel, Word, PowerPoint, Teams, PowerBI) power user
  • Experience working with FICO / TSYS / CGI decision systems (TRIAD, OM, ACE, CACS)

What's in it for you?

  • An inclusive & collaborative working environment that encourages creativity, curiosity, and celebrates success!
  • We offer a competitive rewards package: Performance bonus, Employee Share Ownership Program, and Pension Plan Matching, Health Benefits from day one!
  • Your career matters! You will have access to career development and progression opportunities.

Location(s):  Canada : Ontario : Toronto 
Scotiabank is a leading bank in the Americas. Guided by our purpose: "for every future", we help our customers, their families and their communities achieve success through a broad range of advice, products and services, including personal and commercial banking, wealth management and private banking, corporate and investment banking, and capital markets.  
At Scotiabank, we value the unique skills and experiences each individual brings to the Bank, and are committed to creating and maintaining an inclusive and accessible environment for everyone. If you require accommodation (including, but not limited to, an accessible interview site, alternate format documents, ASL Interpreter, or Assistive Technology) during the recruitment and selection process, please let our  Recruitment team know. If you require technical assistance, please click here. Candidates must apply directly online to be considered for this role. We thank all applicants for their interest in a career at Scotiabank; however, only those candidates who are selected for an interview will be contacted.

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