Senior Quantitative Analyst

Senior Quantitative Analyst page is loaded## Senior Quantitative Analyst remote type:
Hybrid locations:
Toronto, Ontario:
Markham, Ontario time type:
Full time posted on:
Posted Todaytime left to apply:
End Date:
January 30, 2026 (30+ days left to apply) job requisition :
R 1459481
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* Work Location:

** Toronto, Ontario, Canada
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* Hours:

** 37.5
** Line of Business:
** Analytics, Insights, & Artificial Intelligence
** Pay Details:
** 76, CADTD is committed to providing fair and equitable compensation opportunities to all colleagues. Growth opportunities and skill development are defining features of the colleague experience  compensation policies and practices have been designed to allow colleagues to progress through the salary range over time as they progress in their role. The base pay actually offered may vary based upon the candidate's skills and experience, job-related knowledge, geographic location, and other specific business and organizational needs.

As a candidate, you are encouraged to ask compensation related questions and have an open dialogue with your recruiter who can provide you more specific details for this role.
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* Job Description:

** The Model Validation (MV) group is a centralized model risk management function within the Bank. It has seen fast growth in the past few years reflecting global regulators’ increasing attention on model risk. The Retail model validation team within MV is responsible for the vetting and approval of complex mathematical and statistical models used to measure the risk exposure inherent in retail and trading products, as well as to review, validate and approve models used for the calculation of risk capital for these businesses.

By ensuring an objective and independent evaluation of models, the model validation function is critical to the effective measurement and management of risk across the TD Bank Group.
** Job Description**:

The position reports to Senior Manager, Retail Credit Risk, Model Validation
* Perform validation of all models deemed in-scope by the bank-wide Model Risk Policy. These models are used in the Bank for projecting RWA capital (PD/LGD/EAD), Pre-Provision Net Revenue (PPNR) estimates for stress testing (DFAST, EWST) purposes, adjudication/management/collection for various retail products, marketing and analytics, etc.
* Develop independent benchmarks for use in the validation of the above listed models. These benchmark models could be supervised learning, unsupervised learning and deep learning algorithms. Assess the appropriateness of the model for its specific use, reasonableness of the model assumptions and the accuracy of the model implementation.
* Prepare detailed reports describing the mathematical analytics of the model, validation techniques employed, test results obtained, and any model limitations noted.
* Prepare Management summaries highlighting the outcome of the validation process for each model and outlining recommendations for approval or further improvements.
* Establish and maintain productive working relations with internal model development groups such as US and CAD Retail Model Development, Financial Stress Testing (FST), etc., as well as external vendors who have developed customized models for TD.
* Play a key role in ensuring the appropriate use of risk models. Identify the need to implement new models/techniques for risk management as industry standards evolve and regulatory requirements change.
* Stay current in knowledge of credit risk management methodologies, predictive modeling and statistical analysis.
** Requirements and/or qualifications**:
* Strong statistical background and excellent analytical and problem solving skills with a graduate degree in one or more of the following areas: statistics, economics, finance, mathematics, computer science and engineering.
* 3-5 years of experience with model development/validation, including machine learning models, dealing with PPNR stress testing, scorecard and/or capital models
* Hands-on experience with relevant programming languages, such as Python, SAS, R is a must
* Knowledge in retail banking products, customer behaviours, and macroeconomic impacts is a definite asset
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