Job Description
Gauntlet leads the field in quantitative research and optimization of DeFi economics. We manage market risk, optimize growth, and ensure economic safety for protocols facilitating most spot trading, borrowing, and lending activity across all of DeFi, protecting and optimizing the largest protocols and networks in the industry. We build institutional-grade vaults for decentralized finance, delivering risk-adjusted onchain yields for capital at scale. Designed by the most vigilant, quantitative minds in crypto and informed by years of research. As of April 2025, Gauntlet manages risk and incentives covering over $42 billion in customer TVL.\n\nGauntlet continually publishes cutting-edge research that informs our risk models, alerts, and analysis, and is among the most cited institution — including academic institutions — in terms of peer-reviewed papers addressing DeFi as a subject. We’re a Series B company with around 75 employees, operating remote-first with a home base in New York City.\n\nOur mission is to drive adoption and understanding in the financial systems of the future. The unique challenges of decentralized systems call for innovative approaches in mechanism design, smart contract development, and financial product utilization. Gauntlet leads in advancing this knowledge, ensuring safe progression through the evolving landscape of financial innovation.
Requirements
- Minimum 4 years of direct hands-on experience trading or analyzing financial markets (crypto or traditional) professionally.
- Experience developing statistical or quantitative models for financial markets.
- Understanding of blockchain and DeFi protocols, concepts, and best practices (or a strong desire to learn).
- Proficient at writing code in Python and SQL with a solid understanding of software engineering principles.
- Knowledge of workflow orchestration (e.g., Dagster, Airflow) and distributed data processing technologies (Spark).
- Excellent understanding of statistical modeling, machine learning, and optimization algorithms.
- Experience with scientific computing packages such as Numpy/Scipy, Pandas, etc.
- Ability to quickly internalize abstract concepts in new domains, coupled with strong problem-solving skills and attention to detail.
- Ability to work independently and within a team, manage multiple projects, and meet deadlines.
- Strong communication skills and the ability to work collaboratively in a distributed team environment.