VP, Financial Risk Data Governance

About the role

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

VP, Financial Risk Data Governance. The Data Office is on an exciting journey to enhance the quality, control, and accessibility of risk data so business and risk partners can make timely, well-informed decisions. We seek a candidate with deep financial risk domain expertise and a strong understanding of how risk is measured and reported. This is not a technical or analytics role. The selected candidate will act as a business subject matter expert on financial risk data (i.e., credit risk, liquidity risk, market risk and/or interest rate risk), while partnering with risk stakeholders to improve the clarity, quality and controls on the data. This role is expected to act as the team-lead or manager for a small team (2-6 individuals).

Visa sponsorship/support is based on business needs. We do not anticipate providing visa sponsorship/support for this position.

Responsibilities

• Define and maintain clear business definitions, usage rules, and ownership for the data
• Ensure data reflects the true business intent and operating reality of financial risk processes across one or more of the following domains: credit risk, liquidity risk, market risk, and/or interest rate risk
• Identify where process gaps, manual workarounds, or inconsistent practices lead to data quality issues
• Help prioritize and resolve data issues
• Support data quality monitoring, reconciliations, root cause analysis, and issue remediation efforts
• Increase transparency into how credit risk, liquidity risk, interest rate risk, and market risk data is sourced, defined and used across