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Sr. Analyst, Model Validation

Enterprise Data & Analytics
Toronto, ON
May 13, 2022

Company Overview

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Department Overview

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 computing credit risk, and Economic and Regulatory Capital (e.g. Probability of Default, Exposure at Default, Loss Given Default), conducting stress testing (CCAR, EWST), for adjudication of retail products, detecting fraud behaviors, marketing retail products, or projecting Pre-Provision Net Revenue (PPNR) estimates and 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 TDCT Retail Risk Management, TDBNA Retail Credit Risk Analytics, and TD Auto Financing, 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.


  • 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.
  • Experience with predictive model development and/or statistical scorecard modeling
  • Hands-on experience with SAS and/or other sophisticated statistical model development tools (such as Python, R) is a must
  • Knowledge in retail banking products, customer behaviours, and credit adjudication systems is a definite asset
  • Excellent verbal and written communication skills
  • Good time management and multitasking skills
  • Quick learner who grasps new concepts and techniques quickly
  • Must be a good team player

Additional Information

Specific Educational Requirements / Accreditations:

  • Graduate degree in Statistics, Actuarial Sciences, Econometrics, Computer Science or other related fields.
  • Previous experience with TD retail products or modelling would be a great asset.




At TD, we are committed to fostering an inclusive, accessible environment, where all employees and customers feel valued, respected and supported. We are dedicated to building a workforce that reflects the diversity of our customers and communities in which we live and serve. If you require an accommodation for the recruitment/interview process (including alternate formats of materials, or accessible meeting rooms or other accommodation), please let us know and we will work with you to meet your needs.