Model Risk Management Analyst, AVP

Discover your opportunity with Mitsubishi UFJ Financial Group (MUFG), one of the world’s leading financial groups. Across the globe, we’re 150,000 colleagues, striving to make a difference for every client, organization, and community we serve. We stand for our values, building long-term relationships, serving society, and fostering shared and sustainable growth for a better world.

With a vision to be the world’s most trusted financial group, it’s part of our culture to put people first, listen to new and diverse ideas and collaborate toward greater innovation, speed and agility. This means investing in talent, technologies, and tools that empower you to own your career.

Join MUFG, where being inspired is expected and making a meaningful impact is rewarded.

The AVP, Model Validation Quantitative Analyst within the Quantitative Risk Control (QRC) supports best-practice model risk activities consistent with the MUFG Model Governance Program. The models include those used within the various Business Units for supporting Global trading, lending, pricing, Securitization, and Capital market activities.

Model Risk Management:

• Developing, maintaining, and implementing the Bank's Model Risk Management Program covering Wholesale Credit risk models which are used for supporting risk scoring, decision-making, stress testing, ALLL/CECL/IFRS 9, economic capital estimation, financial reporting, and risk management


• Monitor model performance reports on an on-going basis to ensure models remain valid


• Applying strong risk knowledge to solve problems independently, without relying on daily supervision

• Perform independent validations of various models developed based on statistical analysis and machine learning techniques


• Document the validation outcome in high-quality validation report and manage resolution of findings with model developers

• Conduct model/non-model assessment


• Issue/finding closure, and model annual review

• Support relationship with regulators and internal audit


• Team player, ability to communicate technical concepts to non-technical audience 

• Strong skills in quantitative methods including statistical analysis, and credit risk modeling


• Strong skills in quantitative methods and computer technology, such as Python, R and SAS


• 3-5 years' experience in related field


• Strong understanding of financial services industry 


• Strong verbal/communication skills


• Attention to details

• Advanced degree of Masters or higher in statistics, finance, or other quantitative field


• Industry certifications a plus (e.g., CFA, FRM)

Each of MUFG Bank Canada and MUFG Securities Canada is an equal opportunity employer.

• As a federally regulated entity, MUFG Bank Canada is required to comply with applicable laws which prohibit discrimination based on protected grounds and which require accommodation to individuals in accordance with the requirements outlined in the Canadian Human Rights Act and the Canada Labour Code. Where MUFG Bank Canada obtains information relating to protected grounds under the Canadian Human Rights Act as part of the application process, it does so to monitor and otherwise evaluate its own compliance with such legislation and associated regulatory requirements; MUFG Bank Canada does not use such information for decision making purposes relating to the position contemplated in this application.

• As a provincially regulated entity, MUFG Securities Canada is required to comply with applicable laws which prohibit discrimination based on protected grounds and which require accommodation to individuals in accordance with the requirements outlined in the Human Rights Code (Ontario) and the Employment Standards Act (Ontario). Where MUFG Securities Canada obtains information relating to protected grounds under the Human Rights Code (Ontario) as part of the application process, it does so to monitor and otherwise evaluate its own compliance with such legislation and associated regulatory requirements; MUFG Securities Canada does not use such information for decision making purposes relating to the position contemplated in this application.