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Vice President, Quantitative Credit Risk Modeler
Vice President, Quantitative Credit Risk ModelerSmbc Global Foundation Inc • Jersey City, NJ, US
Vice President, Quantitative Credit Risk Modeler

Vice President, Quantitative Credit Risk Modeler

Smbc Global Foundation Inc • Jersey City, NJ, US
2 days ago
Job type
  • Full-time
Job description

Vice President, Quantitative Credit Risk Modeler

SMBC Bank is seeking a highly skilled Vice President, Quantitative Credit Modeling to join our dynamic team in New York City. This role focuses on the quantitative model development, validation finding remediation, and maintenance of advanced credit risk models for wholesale and commercial portfolios, ensuring alignment with regulatory requirements (e.g., CCAR / DFAST, CECL, Basel III / IV) and business objectives. The ideal candidate will possess strong technical expertise in quantitative modeling, a deep understanding of regulatory frameworks, and the ability to collaborate across risk, finance, and technology teams.

Location : Jersey City, NJ, US, 07311 Charlotte, NC, US, 28202 Employment Type : Full Time

The anticipated salary range for this role is between $155,000.00 and $195,000.00. 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

Model Development & Implementation

  • Design, develop, and calibrate credit risk models (such as PD, LGD, EAD) for wholesale / commercial / consumer portfolios, including stress testing (CCAR / DFAST), CECL, and Basel III / IV-compliant risk rating frameworks.
  • Lead end-to-end development of CCAR / DFAST stress testing processes, including data acquisition and processing, variable transformation, estimation, and calibration. Enhance existing models by implementing improvements based on back-testing outcomes, sensitivity analyses, and new data trends.
  • Support regulatory submissions and address feedback from examiners (e.g., FRB, OCC)

Regulatory Compliance & Stress Testing

  • Lead end-to-end execution of CCAR / DFAST stress testing processes, including scenario design, macroeconomic variable selection, and loss forecasting.
  • Ensure models comply with CECL accounting standards and Basel III / IV capital adequacy requirements.
  • Support regulatory submissions and address feedback from examiners (e.g., FRB, OCC).
  • Model Governance & Validation

  • Design and execute comprehensive back testing exercises to assess model performance under varying economic scenarios.
  • Collaborate closely with the model risk and model validation teams to ensure rigorous testing, well-documented methodologies, and compliance with internal and regulatory standards.
  • Perform ongoing model monitoring, back-testing, and sensitivity analysis to ensure robustness across economic cycles.
  • Document methodologies, assumptions, and limitations to meet audit and regulatory standards.
  • Cross-Functional Collaboration

  • Partner with credit officers, finance, and IT teams to operationalize models into underwriting, pricing, and capital planning workflows.
  • Present model results and strategic recommendations to senior management and risk committees.
  • Innovation & Industry Trends

  • Stay current with advancements in credit risk modeling (e.g., AI / ML applications, climate risk integration).
  • Benchmark against industry best practices and peer institutions.
  • Qualifications and Skills

    Education : Master's or PhD in Quantitative Finance, Statistics, Economics, Mathematics, or a related field.

    Experience : 5+ years of experience in credit risk modeling, with a focus on wholesale or consumer portfolios. Proven track record in developing regulatory-compliant models (CCAR, CECL, Basel III / IV). Experience with large datasets and familiarity with banking products (e.g., corporate loans, CRE, leveraged finance).

    Technical Skills : Proficiency in Python programming languages and database tools (SQL, PySpark). Expertise in statistical methods : regression analysis, time series forecasting, machine learning (e.g., XGBoost, TensorFlow). Knowledge of credit risk platforms (e.g., Moody's RiskCalc, CreditEdge) and cloud environments (AWS, Azure) is preferred.

    Certifications (Preferred) : FRM (Financial Risk Manager), CFA, or CRC (Credit Risk Certification).

    Soft Skills : Strong communication skills to translate technical concepts for non-technical stakeholders. Ability to manage multiple priorities in a fast-paced regulatory environment.

    SMBC's employees participate in a Hybrid workforce model that provides employees with an opportunity to work from home, as well as, 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 accommodations@smbcgroup.com.

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