Senior Analyst, Model Validation

Senior Analyst, Model Validation page is loaded## Senior Analyst, Model Validation locations:
Toronto, Ontario time type:
Full time posted on:
Posted Todayjob requisition :
R24017
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* Who we are:

** Fairstone Bank and its family of brands are united in delivering innovative, accessible and reliable financial solutions that enable Canadians to reach their goals. Over the years, our brand family has grown. In 2024, Home Trust Company, Home Bank and Oaken Financial became part of the Fairstone Bank family of brands, alongside Fairstone, Eden
* Park* and Fig.

Together, we are the leading alternative lending bank in Canada. We have the collective experience and expertise to better serve our customers and foster our partners’ growth. With a diverse suite of products—residential and commercial mortgages, consumer deposits and GICs, credit cards, retail and automobile financing, personal loans and digital lending—we offer financial solutions tailored to all Canadians, including newcomers, small-business owners, smart investors and savvy consumers.

Backed by nearly a century of lending experience through its legacy companies, Fairstone Bank and its brand family are proud to be Canada’s leading alternative lending bank.
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* About the role:

** Reporting to Manager, Modeling & Validation, this individual will work on projects related to the management of end-to-end model lifecycle, from development, validation, implementation, monitoring, and maintenance of credit risk scoring models. The ideal candidate should have practical experience in building predictive models using statistical methods such as logistic/linear regression & advanced techniques using AI, validating models to mitigate the model risks under the model governance, as well as excellent data manipulation skills in SAS & SQL or Python.
** Primary

Roles & Responsibilities :
*** Develop and validate custom risk management & marketing models using various modeling techniques including Decision Trees, Logistic Regression, and advanced Machine Learning algorithms
* Support the model validation team to mitigate the model risks. Discovers and diagnoses modeling related risks including input data, assumption, concept, methodology, process, and implementation. Provides subject matter expertise on model's strength and weakness and recommend practical solutions
* Discusses validation results with model owners and governance team to gain consensus and create strategies to implement changes if needed
* Develops validation strategies and plans to ensure appropriate type and level of vetting of models is carried out.
* Independently validates / tests models and their associated assumptions, benchmarks, and supporting documentation against model vesting process, standards, guidelines and principles; assesses the data for model development as well as inputs to the model; compares validation results with model developer results for replicability.
* Identifies deficiencies, conditions for model use, recommends changes, and escalates as required; quantifies model risks, documents outcomes and communicates with stakeholders.
* Identifies where corrective actions are required and escalates per guidelines; monitors and ensures corrective action is taken.
* Provides technical advice and guidance to assigned business/group on implementation of the model vetting framework, and resolution of model risk issues.
* Develops and maintains in-depth knowledge of business and related risk management requirements and legislative/ regulatory directives and guidance.
* Builds effective relationships with internal/external stakeholders.
* Ensures alignment between stakeholders.
* Monitors and tracks performance; addresses any issues.
* Coordinates and monitors the review and sign-off of model validation reporting including model inventory and model inventory attestations.
* Keep abreast of new statistical and machine learning techniques and tools, and industry best practices to predictive modeling.
* Provide technical guidance, proactive support, and data-driven recommendations to management from predictive modeling perspective.
* Communicate and present key findings to both technical and non-technical…