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Develop counterparty exposure models for MUFG’s banking arm – join our Risk Analytics Group in Bengaluru.
Expertise in Python, R, Monte Carlo, and quantitative risk required – apply now.
Position details
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.
Risk Analytics Group (RAG) is a specialized area within the Risk Department, responsible for Market Risk Models, Capital Models, Counterparty Exposure Models, Portfolio and Credit Models, and Initial Margin models. The team members have strong quantitative skills and the team head reports to the regional and global Chief Risk Officer.
The successful candidate will be a member of the Counterparty Exposure Metrics sub‑team of RAG. The team is responsible for the development and maintenance of the Potential Future Exposure (PFE) models that are used to measure Counterparty Exposure. These models are used for internal control limits and partly in economic capital calculations. The PFE is models cover Rates, FX, Credit, inflation, Equity and Bond Spreads, across derivatives, Repo and Securities lending transactions.
Additionally, the team also has responsibility for the SIMM model used for Initial Margin, simulation models used to measure risk on structured financing trades and front office xVA models.
The candidate will work closely with other team members in RAG, credit risk management, the IT development teams, risk model validators and Front Office. The successful candidate will work in an inclusive and proactive way, ensuring that the team takes the lead in new model development and resolves issues as they arise, communicating clearly in management reports.
Roles and Responsibilities
- Support the development, maintenance, and continuous enhancement of counterparty exposure models.
- Develop analytical methodologies and model enhancements to improve the accuracy, robustness, and efficiency of exposure measurement.
- Design and execute model testing and validation analyses, including assessment of model assumptions, methodology, implementation, and performance.
- Investigate model issues and limitations, identify root causes, and recommend appropriate remediation or enhancement activities.
- Specify, test, and support the implementation of system and model changes required to deliver model improvements.
- Develop and enhance operational controls and monitoring processes to strengthen the governance and robustness of exposure models.
- Support business, credit risk, and other stakeholders in analysing and resolving queries relating to exposure calculations and model outputs.
- Collaborate with Market Risk Analytics, Model Validation, and other partner teams on model enhancements, investigations, and strategic initiatives.
- Prepare management information, model performance reporting, and materials for working groups, committees, and governance forums.
- Contribute to ad‑hoc analytical investigations, regulatory initiatives, and strategic projects as required.
Job Requirements
Minimum 4 years of relevant experience in quantitative analytics, model development, model validation, counterparty risk, market risk, or a related risk management function within a financial institution.
Understanding of financial markets and products, including derivatives.
Knowledge of derivatives pricing principles and quantitative modelling techniques.
Knowledge of probability theory, stochastic processes, and stochastic calculus.
Proficiency in analytical and programming tools such as Python, R, Excel, and VBA.
Strong analytical, problem-solving, and communication skills.
Master's degree or higher in a quantitative discipline such as Mathematics, Statistics, Engineering, Computer Science, Physics, Financial Mathematics, Quantitative Finance, or a related field.
Understanding of counterparty credit risk methodologies and exposure measures, including Expected Exposure (EE), Potential Future Exposure (PFE), and Credit Valuation Adjustment (CVA).
Experience in a quantitative risk, counterparty risk, market risk, or model risk management role within the banking industry.
Experience with Monte Carlo simulation techniques and exposure modelling frameworks.
Knowledge of object-oriented programming languages such as C# or C++.
Professional qualifications such as FRM, CQF, CFA, or equivalent.
Mitsubishi UFJ Financial Group (MUFG) is an equal opportunity employer. We view our employees as our key assets as they are fundamental to our long‑term growth and success. MUFG is committed to hiring based on merit and organsational fit, regardless of race, religion or gender.