Quantitative Risk Researcher
DivineArgentina1 day ago
Full-timeFinance, Sales
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Traditional credit was built for people who already have money. Requirements for credit history, collateral, and costly underwriting create insurmountable barriers for those who need capital most—over 1.4B people lack access to credit. A vendor in Lagos earns cash daily but can't prove a steady income. A Colombian nurse with years of perfect informal repayments remains invisible to banks. Most lending systems spend a lot to guess who will repay—and yet so many who are creditworthy still can’t get a loan.
We built Credit to work differently—to reveal creditworthiness through a borrower’s actual behavior. Since launching in December 2024, Credit has issued over 175,000 loans to more than 100,000 unique borrowers using stablecoins on World Chain, with decisions and settlement in seconds and no paperwork, collateral, or data beyond a wallet address.
Join us in advancing open, fair credit.
About The Role
We seek a talented individual to contribute to the risk engineering behind Credit, our leading undercollateralized lending system. You'll work on models that impact hundreds of thousands of users worldwide. You'll also develop tools for quantifying and monitoring risk.
Stack
We built Credit to work differently—to reveal creditworthiness through a borrower’s actual behavior. Since launching in December 2024, Credit has issued over 175,000 loans to more than 100,000 unique borrowers using stablecoins on World Chain, with decisions and settlement in seconds and no paperwork, collateral, or data beyond a wallet address.
Join us in advancing open, fair credit.
About The Role
We seek a talented individual to contribute to the risk engineering behind Credit, our leading undercollateralized lending system. You'll work on models that impact hundreds of thousands of users worldwide. You'll also develop tools for quantifying and monitoring risk.
Stack
- Python
- TypeScript
- Grafana/Prometheus
- Statistical modeling tools
- SQL
- Design, maintain, and optimize credit risk models
- Analyze historical loan performance to calibrate risk parameters
- Develop tools, alerts, and analytics to test, validate, and monitor risk and user behavior
- Collaborate with engineering to implement quantitative models in production
- Research and propose model improvements based on emerging data patterns
- Master's or Ph.D. in a quantitative field such as mathematics, statistics, economics
- Strong expertise in credit risk modeling
- Track record of developing risk models deployed in production at scale
- Strong ability in Python, SQL, and programming for data analysis
- Exceptional problem-solving skills and attention to detail
- Experience with DeFi protocols, especially lending or credit systems
- Familiarity with blockchain data indexing and onchain analytics
- Experience managing and optimizing a loan portfolio
Key Skills
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