Quantitative Analyst

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 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.

Responsibilities:

Statistical Modeling - responsibilities include:

• Developing and maintaining credit risk Scorecard models, including but not limited to Probability of Default and Loss Given Default Models.
• Playing a key role in advancing the Machine Learning initiatives including data collection and preparation, feature engineering, parameter tuning, and exploring academia for new approaches.
• Working with model validation and governance teams to develop methods and metrics for relevant model validation.
• Creating reports and presentations for the Group Manager and Senior Management.

Technical Skills:

• Strong programming skills in at least one of Python, SAS, or R.
• Strong skills in statistical modeling and machine learning methods, including Regression (Linear/Logistic etc.), Decision Tree models such as Gradient Boosting Machines, and Neural Networks.
• Proficient in data querying languages: SAS/SQL.
• Proficient in Microsoft Office Programs: Word, PowerPoint, and Excel.

Qualifications:

Bachelor’s degree or higher in a quantitative or computer programming field such as Quantitative Finance, Economics, Statistics, or Computer Science.

Relevant experience in financial/economic modeling and/or Scorecard modeling preferred through prior internship, undergraduate/graduate level research, or work position.