Vice President, Counterparty Credit Risk Modeling

SMBC Group; Jersey City (NJ); On-site; USD 189,000 - 195,000; Full time

Benefits offered by this job

Annual discretionary incentive

Benefits package

Hybrid work model

Job summary

SMBC Group in Jersey City, NJ is seeking a Vice President to lead counterparty credit risk modeling. The role entails developing, enhancing, and maintaining CCR models across asset classes, with emphasis on regulatory compliance and model governance.

You will collaborate with Risk IT and the front office to productionize models and design comprehensive stress tests. The position requires a Master’s degree with 8+ years of experience in CCR modeling, PFE, and Monte Carlo simulations, using Python

Qualifications

• Master’s degree in mathematics, statistics, or related field with 8 years of experience.
• Experience in CCR modeling, including PFE and margin exposure measures, and stress testing scenarios.
• Proficiency in Python for quantitative modeling, data analysis, and testing.
• Familiarity with regulatory standards governing counterparty credit risk models and governance.

Responsibilities

• Lead development and maintenance of CCR models across asset classes with focus on regulatory compliance.
• Evaluate and compare PFE, margin exposure, and Monte Carlo methodologies.
• Lead design discussions on model assumptions and implementation for derivative products.
• Collaborate with Risk IT and front office to integrate models into production systems.
• Design and maintain stress testing scenarios (historical, hypothetical, forward-looking).
• Ensure governance and documentation for model validation, testing, and monitoring.
• Support surveillance and quantitative analyses to inform risk management and regulatory reviews.
• Partner with stakeholders to estimate trade- and portfolio-level exposures for new transactions.

Skills

Counterparty risk modeling

PFE modeling

Monte Carlo simulation

Model governance

Education

Master’s degree in mathematics, statistics, or related field

Tools

Python

Job description

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Vice President, Counterparty Credit Risk Modeling

Job Level: Vice President

Location: Jersey City, NJ, US, 07311

Employment Type: Full Time

Requisition ID: 8655

SMBC Group is a top-tier global financial group. Headquartered in Tokyo and with a 400-year history, SMBC Group offers a diverse range of financial services, including banking, leasing, securities, credit cards, and consumer finance. The Group has more than 130 offices and 80,000 employees worldwide in nearly 40 countries. Sumitomo Mitsui Financial Group, Inc. (SMFG) is the holding company of SMBC Group, which is one of the three largest banking groups in Japan. SMFG’s shares trade on the Tokyo, Nagoya, and New York (NYSE: SMFG) stock exchanges.

In the Americas, SMBC Group has a presence in the US, Canada, Mexico, Brazil, Chile, Colombia, and Peru. Backed by the capital strength of SMBC Group and the value of its relationships in Asia, the Group offers a range of commercial and investment banking services to its corporate, institutional, and municipal clients. It connects a diverse client base to local markets and the organization’s extensive global network. The Group’s operating companies in the Americas include Sumitomo Mitsui Banking Corp. (SMBC), SMBC Nikko Securities America, Inc., SMBC Capital Markets, Inc., JRI America, Inc., SMBC Leasing and Finance, Inc., Banco Sumitomo Mitsui Brasileiro S.A., and Sumitomo Mitsui Finance and Leasing Co., Ltd.

The anticipated salary range for this role is between $189,000.00and $195,400.00. The specific salary offered to an applicant will be based on their individual qualifications, experiences, and an analysis of the current compensation paid in their geography and the market for similar roles at the time of hire. The role may also be eligible for an annual discretionary incentive award. In addition to cash compensation, SMBC offers a competitive portfolio of benefits to its employees.

Role Objectives

• Lead the development, enhancement, and ongoing maintenance of counterparty credit risk (CCR) models across multiple asset classes, with a focus on quantitative rigor, model robustness, and regulatory compliance.
• Enhance Potential Future Exposure (PFE) modeling frameworks by evaluating and comparing alternative modeling methodologies, including Monte Carlo–based approaches, stress testing methodologies, and margin-related exposure models.
• Drive the analysis and modeling of new and complex derivative products within vendor platforms, leading technical discussions on model design, assumptions, and implementation feasibility.
• Collaborate closely with Risk IT and quantitative infrastructure teams to implement new CCR models, enhance existing model components, and ensure accurate integration into production systems. Design, develop, and maintain a broad suite of stress testing scenarios, including historical, hypothetical, and forward‑looking scenarios, to assess counterparty exposure under adverse market conditions.
• Ensure that CCR modeling frameworks and analytical processes comply with internal model governance standards and external regulatory requirements through robust documentation, testing, and ongoing monitoring.
• Perform continuous counterparty surveillance and exposure monitoring, conducting detailed ad‑hoc quantitative analyses to support risk management, model performance assessment, and regulatory reviews.
• Partner with front office and risk stakeholders to evaluate trade‑level and portfolio‑level exposures, support exposure estimation for new transactions, and provide quantitative insight into counterparty risk dynamics.

Qualifications and Skills

• Master’s degree in mathematics, statistics, or a related field and 8 years of experience.
• Experience must include the following: counterparty credit risk modeling, including Potential Future Exposure (PFE), margin-related exposure measures, and simulation-based exposure profiles across asset classes; Monte Carlo simulation, stochastic processes, and numerical methods for modeling risk factors and exposure distributions; design, implementation, and analysis of comprehensive stress testing scenarios, including historical, hypothetical, and forward‑looking scenarios; regulatory standards governing counterparty credit risk models, including model validation, documentation, testing, and ongoing performance monitoring requirements; Python for quantitative modeling, model testing, data analysis, and implementation support; statistical testing, backtesting methodologies, and model performance assessment, including regression, goodness-of-fit, and stability tests; derivative products across asset classes, including the ability to analyze exposure profiles for new and complex products using vendor modeling platforms; collaboration with Risk IT, quantitative infrastructure teams, and front office stakeholders to support model implementation and exposure estimation; foundation in applied mathematics, including stochastic differential equations and numerical partial differential equation (PDE) methods.

The required skills do not need to be maintained over the full term of the required experience and may be gained through employment or graduate studies.

The role is eligible for an annual discretionary incentive award. In addition to cash compensation, SMBC offers a competitive portfolio of benefits to its employees.

For benefit information, please see the Careers page

SMBC’s employees participate in a Hybrid workforce model that provides employees with an opportunity to work from home, as well, from an SMBC office. SMBC requires that employees live within a reasonable commuting distance of their office location. Prospective candidates will learn more about their specific hybrid work schedule during their interview process. Hybrid work may not be permitted for certain roles, including, for example, certain FINRA-registered roles for which in-office attendance for the entire workweek is required.

SMBC provides reasonable accommodations during candidacy for applicants with disabilities consistent with applicable federal, state, and local law. If you need a reasonable accommodation during the application process, please let us know at [e-mail].