Paxos Labs builds enterprise infrastructure that powers the next generation of trusted onchain financial products. We work with the largest financial enterprises in the world to build transparent and verifiable onchain infrastructure that works for end users and everyday financial use cases. If you believe in bringing DeFi and digital assets to the mainstream, consider building your career at Paxos Labs.
We're hiring a Quantitative Researcher to help scale Paxos Labs's DeFi risk analysis capabilities.
The team at Paxos Labs builds DeFi infrastructure that reimagines the way on-chain liquidity strategies are handled. Strategies and risk management are delegated to sophisticated actors who act from compute done in a data rich offchain environment—all the while maintaining on-chain constraints that enforce user safety.
We are looking for a motivated quantitative researcher that can aptly research and deploy extensive knowledge across TradFi and DeFi to execute state-of-the-art risk curation and yield optimization across the DeFi ecosystem.
Most importantly, we are looking for researchers with interests in the following:
Quantitative Risk Analysis
TradFi Trading Strategies
DeFi Trading Strategies
Manage a portfolio of yield generating opportunities across protocols and chain, closely collaborating with our DeFi engineers on execution.
Manage algorithm design and backtesting to produce actionable insights for DeFi portfolio management.
Create frameworks for risk analysis and portfolio optimization.
Monitor data, forecast risk, and design triggers to enter opportunistic strategies or exit black swan events before anyone else in the market.
Deep Knowledge on Risk Management. Financial and statistical concepts to measure risk and optimal portfolio management.
Deep Knowledge on DeFi Protocols. Internal mechanisms of many if not most of these protocols:
Liquid staking protocols (Lido, EtherFi, Kinetiq)
AMMs (Uniswap, Balancer)
Lending protocols (Aave, Morpho Blue, Maple, Term Finance)
Perp DEXs (Hyperliquid, Lighter, GMX).
Auctions/RFQs/Routers (CoW Protocol, UniswapX, 1inch Fusion, Hashflow)
Familiarity with Data Engineering
Experience with managing a book in TradFi or DeFi across equities, tokens, loan books, or other types of strategies.
Experience applying rigorous statistical methods to portfolio analysis.
Joining Paxos Labs means becoming part of a pioneering team at the forefront of financial innovation for the mass market. You will have the opportunity to:
Build the Future: Play a critical role in transforming traditional enterprises with innovative crypto solutions.
Do Impactful Work: Contribute to projects that have a tangible impact on the global financial landscape.
Enable Personal Growth: Benefit from continuous learning and professional development in a rapidly evolving industry with an emphasis on personal career advancement.
Receive Competitive Compensation: Receive a competitive salary and participate in directly in ownership structures that provide top-of-the-line benefits.
Join A Dynamic Team: Thrive in a fast-paced, agile setting where your ideas are valued and your contributions are recognized.
We are a heavily in-person team working in New York City. We prize effective in-person coordination that allows us to move fast. We also consider remote work on a case by case basis.
Once we receive your application, we'll be in touch if we are interested.
Research and deploy trading algorithms by analyzing market data, developing statistical signals and tools, and improving simulations to support high- to mid-frequency trading and live execution.
Collect and interpret environmental samples and data, support due diligence and Massachusetts Contingency Plan reporting, and contribute to fieldwork and project documentation alongside environmental staff and managers.
Develop and optimize analytical methods, execute biochemical testing, troubleshoot assays and instruments, and communicate data-driven findings while supporting compliant laboratory operations and cross-functional project delivery.
Design and deliver real-world healthcare studies, analyse large datasets, and communicate findings to clients and external stakeholders, contributing evidence for publications, health economic models, and health technology assessment.
Post-train open-source LLMs for specialized customer tasks by turning domain-specific data into reward functions, agent environments, evaluations, and training pipelines that improve production models.
