The Role
Architect and improve the protocol’s quantitative risk engine for on-chain real-world asset trading. Responsibilities include modeling margins, liquidation thresholds, funding rates, open-interest caps, and insurance funds; building stochastic stress tests; analyzing post-trade data; and adapting derivatives pricing, VaR, and Greeks for gas-efficient blockchain execution. The role requires expertise in quantitative finance, TradFi derivatives, DeFi market structures, risk systems, market microstructure, Python, and SQL.
Summary Generated by Built In
The company offers a perpetuals DEX platform engineered specifically for Real World Assets that enables trading of set of assets that were previously unavailable on-chain, from gold, copper, to wheat, oil, and forex pairs to the most popular product in DeFi through trade execution at prices fed in via Chainlink’s new Functions product. It builds on the massive growth in on-chain perpetuals, bringing a first-of-its-kind twist through a focus on RWAs.
This company makes it possible for anyone with a digital wallet to trade stocks, commodities, currencies, and crypto with full transparency without brokers, freezes, nor hidden spreads.
They are hiring a Quantitative Trading Analyst ideally based in Portugal, or in Europe (Hybrid remote)
MISSIONS
As a Quantitative Trading Analyst your role is to architect and upgrade the risk management engine that secures the company's protocol. You will be the bridge between Traditional Finance derivatives and DeFi market structures. Your mandate is to rigorously quantify protocol risk, designing systems that allow for high-leverage trading of real-world assets while mathematically ensuring protocol solvency.
This is a perfect role is perfect for someone who is passionate about DeFi, thrives on solving complex mathematical problems at the intersection of TradFi and crypto, and wants to architect the financial engine of on-chain RWA trading.
You will be in charge of :
- Risk Engine Architecture: Architect and backtest core protocol parameters, including maintenance margins, liquidation thresholds, and insurance fund models for diverse asset classes.
- Mechanism Design: Optimize mathematical models for funding rates, open interest caps, and AMM logic to minimize toxic arbitrage and ensure market balance.
- Stress Testing: Build stochastic simulations to test protocol solvency against extreme volatility and black swan events.
- System Optimization: Analyze post-trade data to detect inefficiencies in our oracle or margining systems and engineer quantitative solutions to fix them.
- TradFi-to-DeFi Bridge: Adapt traditional derivative pricing models (VaR, Greeks) into gas-efficient logic suitable for on-chain execution.
Requirements
Quantitative Fluency : Advanced background in Mathematics, Statistics, or Financial Engineering, with strong proficiency in Python (pandas, numpy, scipy).
Dual-Domain Expertise : Deep understanding of both Traditional Finance derivatives (Futures pricing, options theory) AND DeFi primitives (AMMs, Perpetual DEXs).
Risk Systems Experience : Proven track record of building or auditing risk engines, margin models, or liquidation systems in HFT or DeFi.
Market Microstructure : In-depth knowledge of the economics between liquidity providers and takers, including the relationship between inventory risk, spreads, volatility, and credit.
Data proficiency : Experience using SQL for complex data querying.
Preferred Qualifications
Experience with RWA markets (Commodities, FX) and their specific volatility characteristics.
Understanding of smart contract constraints (Solidity/EVM) to ensure your mathematical models are implementable on-chain.
Experience engaging with on-chain oracles (Chainlink, Pyth) and understanding latency risks.
Benefits
- Competitive compensation package
- Opportunity to work with cutting-edge blockchain technology
- Collaborative environment with highly skilled team members
- Flexible work arrangements
- Professional development opportunities
Recruitment process :
- Recruiter/HR interview.
- Quant Manager interview
- Final Interview
Skills Required
- Advanced background in Mathematics, Statistics, or Financial Engineering
- Strong proficiency in Python, including pandas, NumPy, and SciPy
- Deep understanding of traditional finance derivatives, including futures pricing and options theory
- Deep understanding of DeFi primitives, including AMMs and perpetual DEXs
- Proven experience building or auditing risk engines, margin models, or liquidation systems in HFT or DeFi
- In-depth knowledge of market microstructure, liquidity providers and takers, inventory risk, spreads, volatility, and credit
- Experience using SQL for complex data querying
- Experience with real-world asset markets, including commodities and foreign exchange
- Understanding of smart contract constraints, Solidity, and EVM implementation
- Experience with on-chain oracles such as Chainlink or Pyth and latency risks
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The Company
What We Do
The company is a Web3 trading business building a builder-code product on Hyperliquid. Its decentralized technology aims to broaden access to global financial markets spanning crypto, equities, commodities, and other assets. The platform supports on-chain perpetuals trading and has processed more than $65 billion in cumulative volume with over 400,000 registered traders, while scaling backend infrastructure, APIs, data pipelines, real-time delivery, and databases.
