Counterparty Credit Risk Modeling Associate - Hybrid NYC

SMBC; New York (NY); Hybrid; USD 95,000 - 140,000; Full time

Job summary

SMBC is seeking an Associate in Counterparty Credit Risk Analytics in New York. The role focuses on leading model monitoring, BAU support, and enhancements across the CCR analytics framework, including derivatives and SFT valuation methodologies.

A strong quantitative background and programming skills are essential. Ideal candidates have a PhD or Master’s in a quantitative field and 2–5 years of experience in CCR, xVA, or market risk modeling.

Qualifications

• PhD or Master's degree in Financial Engineering, Mathematics, Computer Science, Statistics, or a related quantitative field.
• Professional certifications (e.g. CFA, FRM) are a plus.
• 2-5 years of experience in counterparty credit risk, xVA or market risk modeling.

Responsibilities

• Assist in the development and enhancement of PFE methodologies for both existing and new products.
• Perform model calibration and ongoing monitoring activities, including root-cause analysis of breaches and the development of remediation actions.
• Perform BAU support and ad-hoc analyses to investigate production issues, partnering with IT to implement remediation solutions.
• Participate in UAT and collaborate with IT and data teams to support new business initiatives and system enhancements.
• Work closely with model validation group on model changes and remediation efforts to address validation findings.
• Partner with risk officers, risk reporting and other stakeholders to enhance the overall CCR framework and strengthen risk management practices.

Skills

Analytical skills

Communication skills

Education

PhD or Master’s in a quantitative field

Tools

Python

SQL

Power BI

Job description

SMBC is seeking an Associate in Counterparty Credit Risk Analytics in New York. The role focuses on leading model monitoring, BAU support, and enhancements across the CCR analytics framework, including derivatives and SFT valuation methodologies.

A strong quantitative background and programming skills are essential. Ideal candidates have a PhD or Master’s in a quantitative field and 2–5 years of experience in CCR, xVA, or market risk modeling.