Credit Risk Analyst

About the role

This role focuses on building and maintaining credit risk frameworks for Gauntlet's onchain financial products. The Credit Risk Analyst will underwrite institutional and on-chain credit relationships, developing models for real-world asset (RWA) assets, including probability of default (PD), loss given default (LGD) frameworks, and stress scenarios. A key part of the work involves running due diligence for new credit and asset-issuer relationships, conducting structured protocol reviews, and analyzing historical on-chain data.

The analyst will establish guardrails for each credit product, defining minimum rates, maximum terms, concentration limits, and eligible collateral. This includes designing first-loss buffer sizing for tranched structures. Collaboration with the Capital Markets team is essential for structuring deals, providing credit input on term sheets, and co-designing trust tranches and advance-rate schedules for securitized products.

Ongoing responsibilities include monitoring the portfolio for borrower financial condition, covenant compliance, and delinquency trends, with a focus on early detection of deterioration and remediation. The role also involves stress-testing the book against various scenarios like elevated delinquency and funding-rate shocks to ensure structural protections are robust. Additionally, the analyst will maintain on-chain risk parameters such as supply caps and exposure thresholds, and contribute to shaping credit terms guidance.

The salary range for this position is between $160,000 and $195,000 USD.

Skills that matter here

• credit risk: This role requires extensive experience in credit risk, specifically in underwriting institutional and on-chain credit relationships and building associated risk models.
• structured finance: The analyst will apply structured finance knowledge to design and evaluate securitized products, including trust tranches and advance-rate schedules.
• asset-backed lending: Experience in asset-backed lending is crucial for understanding and modeling RWA assets and their associated credit risks.
• Python: The ability to build or maintain quantitative risk models using Python is a core requirement for this position.
• R: Candidates should have experience with R for developing or managing quantitative risk models.

Who this role suits

• A professional with 3-6 years of experience in credit risk, structured finance, leveraged finance, or asset-backed lending.
• Someone who has direct credit-underwriting experience, including PD/LGD modeling, loss-curve analysis, and stress testing.
• An individual with hands-on exposure to direct lending, warehouse facilities, ABS/CLO structuring, or securitization.
• A candidate who can distill complex credit analysis into clear, actionable recommendations for non-credit stakeholders.

From the employer

• Underwrite institutional and on-chain credit relationships, and build/own the credit models for RWA assets — PD/LGD frameworks, vintage loss curves, advance-rate haircut schedules, and stress scenarios.
• Run the due-diligence gate for new credit and asset-issuer relationships: structured protocol reviews (solvency, oracle infrastructure, governance, security posture), historical on-chain data analysis, counterparty financials and legal structure, redlines, and final deal approval.
• Set the guardrails for each credit product: minimum rate floors, maximum terms, concentration limits per borrower and asset class, eligible collateral, and first-loss buffer sizing for tranched structures.
• Partner with Capital Markets on structuring: credit input on term sheets (rate, term, size, collateral, covenants, margin-call triggers); co-design trust tranches, covenants, advance-rate schedules, and facility limits for securitized products before close.
• Monitor the portfolio: borrower financial condition, covenant compliance, delinquency trends, and NAV integrity; flag deterioration early and work remediation or exit with Capital Markets.
• Stress the book: elevated delinquency, funding-rate shocks, correlated default, and originator failure — validating that structural protections hold under tail conditions.
• Maintain on-chain risk parameters: supply caps, LLTV settings, exposure thresholds, and related controls.
• Shape credit terms guidance (what we can offer, at what rate, term, and collateral conditions) and track emerging yield strategies, protocols, and issuers to give Curation a competitive edge.

• 3–6 years in credit risk, structured finance, leveraged finance, or asset-backed lending at a leading financial institution, credit fund, or fintech lender.
• Direct credit-underwriting experience: PD/LGD modeling, loss-curve and vintage analysis, advance-rate structuring, covenant design, and stress testing.
• Hands-on exposure to one or more of: direct lending, warehouse facilities, ABS/CLO structuring, securitization, asset-backed finance, or structured credit.
• Strong grasp of legal/structural credit concepts: SPV formation, bankruptcy remoteness, security-interest perfection, covenant packages, and waterfall mechanics.
• Portfolio-monitoring experience: delinquency tracking, covenant compliance, borrower financial review, and early-warning systems.
• Exceptional written and verbal communication - able to distill complex credit analysis into clear, actionable recommendations for non-credit stakeholders.
• Experience building or maintaining quantitative risk models in Python or R.

• Remote first - work from anywhere in the US & CAN!
• Regular in-person company retreats and cross-country "office visit" perk
• 100% paid medical, dental and vision premiums for employees
• $1,000 WFH stipend
• Monthly reimbursement for home internet, phone, and cellular data
• Unlimited vacation
• 100% paid parental leave of 12 weeks
• Fertility benefits
• Opportunity for incentive compensation