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Canadian Bank, Auto & Wealth (CBAW) Risk Management is committed to providing timely and accurate risk quantification solutions supporting the Retail, Small Business Bank, Wealth, and Customer Assistance business lines.
The Data & Model Implementation team is part of the Model Management & Analytics (MMA) group within the CBAW Risk Management Centers of Expertise and is responsible for data pipeline implementation and oversight, and model implementation, on-going operational model updates/optimization, and model execution for Canadian and US product portfolios.
As the team continues to transition to a Development Operations model of continuous delivery strong leadership will be required to ensure a clear vision is articulated and implemented as the supporting SAS 9.4 platform is updated in the next 2 years.
The position works closely with MMA teams, Retail Model Development, Layer 6, Model Validation, Technology Solutions, and several internal and external partners with the following key accountabilities:
Lead a growing team of 16 full time, contract, and associate professionals
Lead data discovery and updates to the model scoring data pipeline from multiple internal and external sources
Lead the continuous improvement of the model implementation framework to support existing and new capabilities from downstream data and scoring consumers
Lead expected loss, adjudication, account management, and collections model implementation on complex platform leveraging host and distributed technologies
Support downstream analysis of model results
Collaborate with model development teams and the MMA Reporting team to perform various impact estimates for new model implementations
Support the MMA Governance team and CBAW Risk Management during internal and external audit reviews and compliance attestations
Support the development and execution of a program plan to replatform model operations to a new SAS environment, leveraging new vendor capabilities to help reduce the reliance on internal software development
Expand the scope of data and model implementation and operations to support models implemented on Hadoop
Strong working knowledge and extensive hands-on experience using SAS, SQL, or similar tools in the context of data manipulation, data mining, and statistical analysis
Working knowledge of UNIX/LINIX and familiar with UNIX/LINIX commands and file systems
Good understanding of job automation and optimization
Experience working in both operational and project environments
Strong problem-solving skills, ability to independently identify, debug and solve problems in an effective and timely manner
Good inter-personal skills to build and maintain productive working relationships with various business partners across The Bank and in different levels of the organization
Strong written and oral communication skills
Ability to manage multiple initiatives and priorities, ensuring critical deadlines are met
An understanding of the credit life cycle and related regulatory frameworks would be an asset
Education and Accreditation:
An undergraduate degree in Computer Science, Engineering, or comparable work experience
A graduate degree in management or similar disciplines would be considered an asset
SAS or R certification
PRMIA, GARP, CPA or similar accreditation would also be considered an 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.