Bring your expertise to JPMorgan Chase. As part of Wholesale Credit Risk Loan Loss Forecasting team, you will help influence loan loss estimation and collaborate with risk executives and business stakeholders across the firm to articulate methodology assumptions and forecasting outcomes for exercises including Quarterly Stress Testing (QST), Comprehensive Capital Analysis and Review (CCAR), and ad hoc risk analysis and stress limit management.

As a Risk Associate in Wholesale Credit Risk Loan Loss Forecasting team, you will support the forecasting and stress analytics for a portfolio of credit hedges and held-for-sale loans. Additionally, this role offers a unique opportunity to build deep expertise in various credit products, develop a strong understanding of the firm’s stress testing frameworks and modeling assumptions, and help shape the future stress treatment through close partnership with the Business, Finance, and Quantitative Research teams across JPMorgan Chase. The ideal candidate is passionate about risk management and brings strong quantitative and analytical skills, with experience independently driving projects spanning technology, modeling, and data. The Associate will communicate insights and results to senior stakeholders across the First Line and Second Line of Defense.

Job Responsibilities

• Build and maintain a strong understanding of wholesale credit hedging strategies and instruments, including single-name CDS, indices, options, and Synthetic Risk Transfer (SRT) transactions.
• Review and challenge stress forecasts for hedge P&L and loss-mitigation benefit under internal and regulatory scenarios; support end-to-end stress testing production cycles for Quality Stress testing and Comprehensive Capital Analysis and Review.
• Develop clear, well-structured management presentations summarizing stress results, key drivers, and walk/explain narratives for business and risk stakeholders.
• Partner with Quantitative Research to refine modeling treatments and assumptions; become a subject matter resource on credit loss forecast parameters including Probability of Default, Loss Given Default, Rating Migration, and Mark-to-Market loss.
• Lead UAT and implementation support for model enhancements, system migrations, and new functionality releases, including requirement definition, test design, execution, and issue triage.
• Conduct ad hoc, transaction-level risk and stress estimates, and perform ongoing portfolio monitoring and targeted deep-dives to identify emerging risks and forecast sensitivities.
• Drive process efficiency through automation initiatives (including responsible use of LLMs/AI, where appropriate) to streamline forecasting, reporting, and controls.
• Provide analytical support for risk review and challenge of new products, business initiatives, and stress methodology changes impacting the respective portfolios
• Build and sustain strong stakeholder relationships across Business, Risk, Finance, Quantitative Research, and Technology, ensuring alignment on assumptions, timelines, and deliverables.
• Maintain working knowledge of loan underwriting and syndication activities; stay current on credit market conditions, macro themes, and relevant M&A / event-driven activity impacting the portfolio.

Required Qualifications, Capabilities and Skills

• Bachelor’s degree in Business, Finance, Mathematics, or a related field.

• Minimum 3 years of experience in credit risk, stress testing, risk analytics, model development, or similar roles.

• Demonstrated ability to build effective working relationships across First Line and Second Line stakeholders.

• Ability to work independently with minimal supervision; sound judgment on when to escalate; ability to perform under pressure and deliver under tight deadlines.

• Strong written and verbal communication skills, with experience preparing materials for senior management.

• Strong attention to detail, with the ability to manipulate and analyze large datasets and translate results into clear messaging.

Preferred Qualifications, Capabilities and Skills

• Strong technical skills, especially Excel, Tableau, and experience applying LLMs/AI to improve workflow efficiency; Python and automation experience is a plus.
• Strong knowledge of loan and derivative products; familiarity with credit hedging instruments (CDS/index/options) strongly preferred.