Gauntlet’s mission is to drive adoption and understanding of the financial systems of the future. Gauntlet is the platform for off-chain intelligence that drives on-chain efficiency in Decentralized Finance
(DeFi). We work with protocols to manage risk, improve capital efficiency, and manage incentive spend. We also publish cutting-edge research and aim to take a leading role in defining market risk standards across the industry.
Gauntlet is building infrastructure that allows us to simulate and stress-test blockchain protocols, contracts, and network interactions at scale over a wide range of market conditions. Our models ingest a wide range of on-chain and off-chain data, and are continuously calibrated to the current
crypto market structure so that our recommendations are always up-to-date. These models and infrastructure power our platform that currently manages risk and optimizes incentives for over $40B in assets.
In order to grow our impact in the
DeFi space we are looking to hire experienced Data Scientists to help new and established protocols better understand the systems they’ve built. This role will require establishing a strong ability to analyze and interpret data; as well as the ability to collaborate with and manage external clients. You will be working directly with the leadership of premier and innovative
DeFi protocols and developing expert-level knowledge and experience of the mechanisms that underpin the
DeFi industry.
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 $150,000 - $180,000 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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