Lead Data Analyst, Vice President

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

Discover your opportunity with Mitsubishi UFJ Financial Group (MUFG), the 7th largest financial group in the world. Across the globe, we’re 120,000 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.

Major Responsibilities

• Create new data analytics including the analysis of metrics and risk assessment results, where needed
• Identify opportunities to automate processes for compliance monitoring tool optimization and efficiencies Use statistical methods to analyze data and generate useful business reports
• Work with management team to create a prioritized list of needs for each business segment
• Identify and recommend new ways to save money by streamlining business processes
• Use data to create models
• Work with department managers to outline the specific data needs for each business method analysis project

Qualifications

• Bachelor's degree in Computer Science or a closely-related discipline, or an equivalent combination of formal education and experience
• 6-8 years' work experience doing quantitative analysis
• 3-4 years of experience using SQL, ETL, Informatica, and Python
• Strong financial industry experience
• Expert knowledge in all business processes across an entire line of business, as well expertise in other lines of business and technology disciplines
• Experience working with high-performing teams in complex program execution
• Strong understanding of waterfall and agile methods, stakeholder management, budget management, risk management, and operations
• Ability to create and maintain relationships with a wide range of stakeholders
• Strong project management experience within technology organization
• Hands on project and program management experience; track record of project go live implementations
• Technology infrastructure or application development experience
• Extensive knowledge of data model theory, database design, structured query language (SQL), and related data warehousing practices
• Experience with Cognos and Tableau and their respective consumption of data is preferred
• Use of other data modeling tools will be considered with the core skill set: advanced SQL, Python (descriptive / predictive models), and Tableau Viz
• Streamline and automate processes to ensure data lineage, consistency, integrity, and transparency
• Lead all aspects of requirements analysis, traceability, and testing for enhancements and projects that are small, medium, or large in size and/or complexity, while supporting those functions for large cross-functional or enterprise-wide initiatives
• Perform day-to-day operational support; may mentor other analysts
• Participate in the design and delivery of solutions that support the fundamental data and governance process
• Handle multiple simultaneous data and reporting projects
• Understand and translate business needs into data models supporting long-term solutions
• Work with application developers to implement data strategies, build data flows, and develop conceptual data models
• Create logical and physical data models using best practices to ensure high data quality and reduced redundancy
• Optimize and update logical and physical data models to support new and existing projects
• Maintain conceptual, logical, and physical data models along with corresponding metadata
• Develop best practices for standard naming conventions and coding practices to ensure consistency of data models
• Recommend opportunities for reuse of data models in new environments
• Perform reverse engineering of physical data models from databases and SQL scripts
• Evaluate data models and physical databases for variances and discrepancies
• Validate business data objects for accuracy and completeness
• Analyze data-related system integration challenges and propose appropriate solutions
• Develop data models according to company standards
• Advise colleagues and sta