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MUFG Union Bank Sr. Quantitative Analyst, VP - Hybrid (CA) in Los Angeles, California

Do you want your voice heard and your actions to count?

Discover your opportunity with Mitsubishi UFJ Financial Group (MUFG), the 5th largest financial group in the world. Across the globe, we’re 180,000 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.

This is a hybrid position. There are flexible work from home options available. A member of our recruitment team will discuss the options with you in more detail.

Job Summary:

As a member of the Wholesale Credit Risk Modeling (WCRM) team, this role is intended for model developers with strong analytic skills, having 3 to 5 years of relevant credit and/or market risk modeling or risk management experience. In support of the Bank’s overall credit risk management framework, WCRM develops and manages a wide-ranging inventory of models covering all aspects of credit loss analysis, including advanced internal ratings based methods, and PD, LGD, and EAD models covering C&I, CRE, and specialty industries.

Major Responsibilities:

Risk measurement, analysis, and methodology design including

  • Developing, documenting, implementing or otherwise enhancing models for credit loss

  • Working closely with business line and risk managers to assess and manage firm wide risk

  • Working with model governance teams to develop methods and metrics for performance monitoring, ensuring all models continue to perform as expected and within ranges agreed to by internal model audit and model validation groups

Thought leadership, research, and ad hoc analysis:

  • Expected to stay informed of research trends and market best practices, share information with the teams and management

  • Explore opportunities for increased efficiencies through automation

  • Critically evaluate, develop and deploy systematic methodology improvements.

  • Explore machine learning modeling techniques as alternatives to traditional methods

  • Validate methodologies of vendor purchased models and tools and related infrastructure to inform modeling strategy


  • Graduate degree in a quantitative discipline MSc, MMF or Ph.D. (physics, finance, economics, econometrics, statistics, mathematics, or equivalent experience.)

  • Three to five years of relevant business experience in credit and/or market risk, risk management

  • Well-developed project management and communication skills

  • Strong programming and database experience (e.g., Python, R, SAS/SQL)

  • Well-developed relationship management skills and excellent written and verbal communication

  • Ability to work in a dynamic environment under pressure and undertake, execute and deliver on time multiple concurrent projects

The above statements are intended to describe the general nature and level of work being performed. They are not intended to be construed as an exhaustive list of all responsibilities duties and skills required of personnel so classified.

We are proud to be an Equal Opportunity/Affirmative Action Employer and committed to leveraging the diverse backgrounds, perspectives and experience of our workforce to create opportunities for our colleagues and our business. We do not discriminate on the basis of race, color, national origin, religion, gender expression, gender identity, sex, age, ancestry, marital status, protected veteran and military status, disability, medical condition, sexual orientation, genetic information, or any other status of an individual or that individual’s associates or relatives that is protected under applicable federal, state, or local law.