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Freelance Credit Risk Modeling Jobs (NOW HIRING)

Gauntlet

Credit Risk Analyst

New York, NY · On-site

This is not a seat where you inherit a model and press run. You will define the underwriting ... The role The Credit Risk team runs due diligence on the assets, protocols, and chains supported by ...

Ryan Specialty

Quantitative Risk Modeling Lead

Position Summary As a Quantitative Risk Modeling Led in the Ryan Credit Solutions department at Ryan Specialty, you will leverage your actuarial and quantitative expertise to shape the underwriting ...

Regional Finance

Manager Credit Risk

Plano, TX · On-site

Mines, models, analyzes large datasets, and utilizes predictive modeling techniques with an emphasis on optimizing credit risk and marketing campaign performance using the following predictive ...

Biz2Credit Inc

Director of Credit Risk

Manhattan, NY

$160K - $190K/yr

Responsibilities Credit Decisioning Model Development * Develop and implement advanced credit risk models (rule-based, heuristic, and machine learning) to support underwriting and portfolio ...

Biz2Credit Inc

Director of Credit Risk

Manhattan, NY · On-site

$160K - $190K/yr

Responsibilities Credit Decisioning Model Development * Develop and implement advanced credit risk models (rule-based, heuristic, and machine learning) to support underwriting and portfolio ...

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Freelance Credit Risk Modeling information

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$187.5K

How much do freelance credit risk modeling jobs pay per year?

As of Jul 16, 2026, the average yearly pay for freelance credit risk modeling in the United States is $145,100.00, according to ZipRecruiter salary data. Most workers in this role earn between $132,500.00 and $148,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Freelance Credit Risk Modeler, and why are they important?

To thrive as a Freelance Credit Risk Modeler, you need a strong background in statistics, quantitative finance, and data analysis, typically supported by a degree in finance, mathematics, or a related field. Proficiency in programming languages such as Python, R, or SAS, along with experience using risk modeling software and knowledge of regulatory frameworks like Basel III, is crucial. Excellent communication, project management, and client relationship skills help distinguish top freelancers in this role. These abilities are essential for delivering accurate risk assessments, meeting client expectations, and maintaining compliance in a dynamic financial environment.

What is freelance credit risk modeling?

Freelance credit risk modeling involves independent professionals analyzing and predicting the likelihood that borrowers or counterparties will default on financial obligations. These freelancers use statistical methods, machine learning models, and data analysis to assess credit risk for banks, lenders, or other firms. Their work helps organizations make informed lending decisions, set appropriate interest rates, and comply with regulatory requirements. Freelancers in this field may work on projects like developing credit scorecards, stress testing portfolios, or validating existing risk models.

What is the difference between Freelance Credit Risk Modeling vs Credit Analyst?

AspectFreelance Credit Risk ModelingCredit Analyst
CredentialsRelevant certifications (e.g., CFA, credit risk certifications), strong quantitative skillsTypically requires a degree in finance, economics, or related field; certifications are a plus
Work EnvironmentIndependent, project-based, remote or client-siteUsually in banks, financial institutions, or corporate offices
Industry UsageUsed by consulting firms, freelance platforms, and financial servicesEmployed directly by financial institutions or corporations
Comparison Search IntentUnderstanding freelance opportunities in credit risk modelingAssessing creditworthiness and risk for lending decisions

Freelance Credit Risk Modeling involves independent, project-based work focusing on developing risk models, often remotely. Credit Analysts work within organizations to evaluate creditworthiness, typically in a structured environment. While both roles require financial expertise and similar credentials, their work settings and employment types differ significantly.

How do freelance credit risk modelers typically collaborate with clients and other stakeholders during projects?

Freelance credit risk modelers usually work closely with client teams such as credit analysts, data engineers, and compliance officers to understand data sources, project objectives, and regulatory requirements. Communication often occurs through regular virtual meetings, progress reports, and collaborative tools to ensure transparency and alignment. Freelancers must be proactive in clarifying goals, sharing preliminary findings, and incorporating feedback to deliver models that meet both technical and business needs. Building strong client relationships and maintaining clear documentation are key to successful collaboration in this role.
More about Freelance Credit Risk Modeling jobs
What cities are hiring for Freelance Credit Risk Modeling jobs? Cities with the most Freelance Credit Risk Modeling job openings:
What are the most commonly searched types of Credit Risk Modeling jobs? The most popular types of Credit Risk Modeling jobs are:
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What job categories do people searching Freelance Credit Risk Modeling jobs look for? The top searched job categories for Freelance Credit Risk Modeling jobs are:
Freelance Credit Risk Modeling jobs near you
Infographic showing various Freelance Credit Risk Modeling job openings in the United States as of July 2026, with employment types broken down into 90% Full Time, and 10% Part Time. Highlights an 80% In-person, and 20% Hybrid job distribution, with an average salary of $145,100 per year, or $69.8 per hour.
Credit Risk Analyst

Credit Risk Analyst

Gauntlet

New York, NY • On-site

Full-time

Medical, Dental, Vision, PTO

Posted 23 days ago

Job description

You will own credit risk for one of the largest asset managers in onchain finance. Gauntlet serves $1.5B+ in client TVL, and every dollar of credit we extend onchain runs through a risk function that is yours to build. This is not a seat where you inherit a model and press run. You will define the underwriting standards, design the frameworks, set the redlines, and be the internal check on every asset-onboarding decision Gauntlet makes, working shoulder-to-shoulder with Capital Markets, Vault Curation, and senior leadership. If you want to build the credit infrastructure for institutional finance moving onchain, rather than maintain someone else's, read on. About Gauntlet

Gauntlet builds the financial systems of the future. While much of onchain finance is focused on point solutions, we operate across the entire stack to offer best-in-class vault products. Today we serve over $1.5B in client TVL across some of the largest fintechs/neobanks, protocols, exchanges, and capital allocators in crypto - and, increasingly, traditional asset management. Our team brings together traditional finance and crypto-native expertise to deliver durable, sophisticated products for institutional clients moving onchain.

The role

The Credit Risk team runs due diligence on the assets, protocols, and chains supported by Gauntlet's lending and vault products, sets the guardrails that govern our lending activity, and monitors credit assets both off-chain and on-chain. You will work the full credit lifecycle - initial diligence and deal structuring through ongoing portfolio surveillance - across direct lending, structured facilities, and on-chain/off-chain securitization. You own the risk models, the parameters, and the monitoring cadence. You partner with Capital Markets on structuring and with Product and Engineering to embed credit controls directly into our on-chain infrastructure.

What you'll do
  • 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.
What success looks like

First 30 days. Ramp on Gauntlet's vault infrastructure, especially on-chain credit structures. Meet stakeholders across Capital Markets, Strategy & Growth, Product, and Engineering, review the current book and pipeline, and form a clear view of the existing DD framework - including its gaps in coverage, model depth, or monitoring cadence.

First 3 months. Operating as the credit-risk owner across active and incoming deal flow: running your own models on the live pipeline (PD/LGD, stress scenarios), producing structured DD memos and go/no-go recommendations for Capital Markets and Vault Curation, and established as the Credit Risk point of contact on at least one active credit product with monitoring cadence and escalation protocols in place.

In 1 year. Reviewed and closed multiple institutional credit relationships across at least two product types. Running a portfolio-monitoring function with consistent cadence (covenant tracking, delinquency surveillance, stress refresh, parameter maintenance). Recognized internally as the authority on Gauntlet's credit standards, with reusable DD playbooks and risk-parameter frameworks that compress future deal cycles for Credit Risk and Capital Markets.

What you bring
  • 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.
Bonus points
  • On-chain credit protocols, DeFi lending markets, or tokenized-asset structures (e.g., Morpho, Aave, tokenized ABS).
  • Crypto-native credit risk: smart-contract risk, oracle failure, depeg events, and on-chain collateral liquidity.
  • Prior work with RWA issuers, fintech lenders, or asset originators - understanding the pipeline and servicing behind the loan tape.
  • Exposure to prime-brokerage credit, repo, or securities financing from a risk perspective.
Who thrives here
  • Naturally curious about digital assets, DeFi, and the evolution of institutional credit. Prior crypto experience is not required - curiosity is.
  • Wants to own the full credit function, not just run models. Comfortable building frameworks from scratch, setting standards, and defending views with Capital Markets and senior leadership.
  • Operates with significant autonomy in an entrepreneurial environment. Wants to build the credit infrastructure, not inherit it.
  • Analytically rigorous but commercially aware - understands the credit function exists to enable deal flow, not block it, and manages that tension thoughtfully.
Benefits and Perks
  • 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
Please note at this time our hiring is reserved for potential employees who are able to work within the contiguous United States and Canada. Should you need alternative accommodations, please note that in your application.
 
The national pay range for this role is $160,000 - $195,000 base plus additional On Target Earnings potential by level and equity in the company. Our salary ranges are based on paying competitively for a company of our size and industry, and are one part of many compensation, benefits and other reward opportunities we provide. Individual pay rate decisions are based on a number of factors, including qualifications for the role, experience level, skill set, and balancing internal equity relative to peers at the company.  
 
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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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