Senior Payments IT Business Analyst (AI & Data Focus), VP

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.

The selected colleague will work at an MUFG office or client sites four days per week and work remotely one day. A member of our recruitment team will provide more details.

Role Summary:

We are seeking a Senior Payments IT Business Analyst with deep expertise in payments technology and data-driven transformation. This role will bridge business, technology, and data/AI capabilities, enabling intelligent decision-making across modern payment platforms.

The ideal candidate brings strong knowledge of payment systems architecture and hands-on experience leveraging AI/ML tools for analytics, reporting, and insights generation to drive efficiency, risk reduction, and enhanced client experience.

Key Responsibilities:

1. Payments Technology & Architecture

• Act as a technology-facing Business Analyst supporting payment platforms across:
  • ACH, Wire, SWIFT, RTP/FedNow, Cross-border payments
• Understand and contribute to system architecture, APIs, event-driven flows, and data pipelines
• Partner with architects and engineering teams to define scalable, resilient payment solutions

2. AI-Driven Analytics & Reporting

• Leverage AI/ML tools and platforms to:
  • Generate insights on payment trends, volumes, and anomalies
  • Automate operational and regulatory reporting
  • Improve reconciliation, exception handling, and productivity
• Design intelligent dashboards and self-service reporting frameworks
• Use tools such as:
  • Python / SQL / Power BI / Tableau
  • AI copilots, LLM-based analytics, or enterprise AI platforms
• Enable predictive analytics (e.g., failure prediction, liquidity forecasting, fraud signals)

3. Business & Data Analysis

• Gather and document functional, technical, and data requirements
• Define:
  • Data mappings (ISO 20022, SWIFT MT/MX)
  • Transformation rules and schemas
• Analyze end-to-end payment lifecycle and identify automation opportunities

4. Stakeholder Collaboration

• Interface with:
  • Business (Treasury, Operations)
  • Technology (Engineering, Architecture, Data teams)
  • Risk & Compliance
• Lead workshops translating business problems into technology + AI-enabled solutions

5. Testing & Implementation

• Define and execute test strategies (SIT/UAT) with focus on:
  • Payment message validation
  • Data accuracy and completeness
• Validate AI/analytics outputs to ensure explainability and auditability

6. Risk, Control & Compliance

• Ensure solutions meet:
  • AML / Sanctions screening requirements
  • Regulatory reporting standards
• Incorporate controls within AI-driven processes (model transparency, audit trails)

Required Qualifications

• 10+ years of experience as IT Business Analyst in payments domain
• Strong understanding of:
  • Payments systems (ACH, Wire, SWIFT, RTP/FedNow)
  • Payment architectures (hubs, APIs, microservices)
• Hands-on experience with:
  • Data analysis tools (SQL, Excel, Python preferred)
  • Reporting tools (Power BI, Tableau, etc.)
• Proven experience using AI/ML or advanced analytics for reporting or operational insights
• Experience with Agile delivery models and JIRA/Confluence

Preferred Qualifications

• ISO 20022 expertise (MT → MX migration, data enrichment)
• Experience with payment platforms (Finastra GPP, EPP, FIS, etc.)
• Exposure to:
  • Cloud (AWS/Azure/GCP) and data platforms (Snowflake, Databricks)
  • Event-driven architecture (Kafka, messaging systems)
• Familiarity with:
  • GenAI tools (Copilots, LLM-base