Additional Information
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.
Job Summary:
As financial crimes compliance continues to evolve alongside rapid advancements in technology, there is an increasing need to bridge traditional compliance expertise with innovative solutions using artificial intelligence machine learning (traditional, agentic, and generative AI) and robotic process automation solutions (Power Automate, Copilot, Copilot Studio). This Compliance Analyst Program (CAP) opportunity supporting the Global Financial Crimes Technology Innovation team has been created to help address our need. The incumbent Analyst will be responsible for evaluating, developing, and implementing emerging technologies that enhance risk detection, operational efficiency, and compliance strategies across the organization. They will concentrate on creating AI and RPA routines using a variety of end user tools including MS Power Automate and Keyence as well as creating models using machine learning Python, R Studio, etc., tools and agents/large language models within cloud infrastructures (e.g., AWS, Azure) working closely with Financial Crimes stakeholders who will advise the use cases corresponding to any internal development for an optimal platform solution. The incumbent will also analyze vendors and conduct trial exercises while working closely with users in all GFCD regions. This role will report to the Head of Global Financial Crimes Early Careers & Resource Operations and sit within the GFCD CAP, which develops early-career talent with broad exposure to financial crimes compliance, data analysis, and risk management practices.
Major Responsibilities:
Work collaboratively across functional teams within GFCD to ensure optimal innovation vendor is selected based on stakeholder requirements
Serve as the initial point of contact with vendors identified as providing innovative solutions to stakeholders
Using end user development skills such as Microsoft Power Automate, Keyence, Python, R Studio, etc., develop end user Robotics and Machine Learning models based on stakeholder requirements.
Using end user development skills associated with agentic and generative models found in AWS and Azure environments, develop end user solutions based on stakeholder requirements.
Using subject matter expert skills associated with cloud environments, identify cloud environment tools that are available to GFCD for native building of solutions (e.g., AWS Bedrock, DataBricks, Azure Open AI, etc.), including pros and cons assessment of environments and available tools.
Support the Innovation team's end user development group by providing maintenance and support services for all group developed automation.
Monitor areas of innovation in the banking industry for proactive financial crime risk identification and ascertain suitability for implementation within MUFG.
Perform continuous evaluation of available solutions that are active in the marketplace or financial space.
Create supporting documentation to evaluate vendors for trial exercises, including interaction with Third Party Risk Management, Software Assessment, and similar MUFG groups.