| Job Position | Company | Posted | Location | Salary | Tags |
|---|---|---|---|---|---|
Divine | San Francisco, CA, United States | $121k - $164k | |||
Token Relations | New York, NY, United States | $91k - $96k | |||
Fundstrat Global Advisors | New York, NY, United States | $100k - $150k | |||
Inversion | New York, NY, United States | $45k - $86k | |||
| Learn job-ready web3 skills on your schedule with 1-on-1 support & get a job, or your money back. | | by Metana Bootcamp Info | |||
Ripple | New York, NY, United States | $53k - $58k | |||
MLabs | New York, NY, United States | $120k - $150k | |||
CoinTracker | United States | $140k - $300k | |||
Selby Jennings | Washington, United States | $75k - $80k | |||
WorkAsPro | United States | $72k - $99k | |||
Chainalysis | New York, NY, United States | $108k - $205k | |||
Hack VC | New York, NY, United States | $150k - $200k | |||
Yuma | Stamford, CT, United States | $105k - $125k | |||
Blockworks | New York, NY, United States | $120k | |||
MLabs | New York, NY, United States | $120k - $150k | |||
MLabs | New York, NY, United States | $120k - $150k |
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 1.4 billion 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.
We built an alternative called Credit. Since December 2024, it has issued hundreds of thousands of undercollateralized loans using stablecoins. People from around the world have used these loans to pay for things like groceries, medicine, and transportation. Backed by $6.6 million from Paradigm and Nascent, we're scaling a system that has already reached half a million unique borrowers. Help us take it to the next level.
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