Risk Analyst | Vaults
Offer summary
Qualifications:
Bachelor’s or Master’s degree in a quantitative field such as Mathematics, Statistics, Physics, Computer Science, Engineering, or Financial Engineering., 2–4 years of experience in quantitative research, trading, or risk modeling, preferably in crypto, DeFi, or finance., Proficiency in Python for quantitative research, including libraries like pandas, numpy, scipy, and plotly., Knowledge of DeFi primitives such as AMMs, lending/borrowing, stablecoins, vaults, and yield farming..Key responsibilities:
- Research and design algorithmic yield strategies for crypto vaults to optimize risk-adjusted returns.
- Assess protocol-specific and systemic risks, including smart contract vulnerabilities and market volatility.
- Develop models to quantify tail risks, VaR, and protocol failure impacts, using Monte Carlo simulations and scenario analysis.
- Collaborate with engineers to implement models, automate rebalancing, and deploy strategies on-chain.
Job description
P2P.org is the largest institutional staking provider with a TVL of over $10B and a market share exceeding 20% in restaking.
Our clients include BitGo, Copper, Crypto.com, Ledger, ByBit, Bitget, OKX, HTX, Bitvavo, SBI, and others, who choose us for our clientcentric approach and extensive product line from unified API to widgets and custom dApps.
P2P.org unites talented individuals globally ❤️
P2P.org boasts a strong reputation and network. We prioritize customer satisfaction and, as tech enthusiasts, develop innovative solutions that bolster our brand.
You will 🚀Research and design algorithmic yield strategies for stablecoin and crypto vaults, targeting riskadjusted yield optimization through leverage, protocol stacking, and dynamic rebalancing.
Quantitatively assess protocolspecific and systemic risks, including smart contract vulnerabilities, liquidity depth, slippage, oracle dependencies, and market volatility impacts across integrated DeFi protocols
Develop probabilistic and scenariobased models to quantify tail risks, VaR, and protocol failure impact; implement Monte Carlo simulations and agentbased modeling to evaluate strategy robustness across historical and synthetic conditions.
Perform stress tests based on extreme market events, flash loan attacks, and stablecoin depegs to validate strategy durability.
Work closely with smart contract and backend engineers to productionize models, automate rebalancing logic, and integrate risk controls directly into vault infrastructure. Ensure strategy logic is safely and efficiently deployed onchain.
You have 🤓Bachelor’s or Master’s degree in a quantitative field such as Mathematics, Statistics, Physics, Computer Science, Engineering, or Financial Engineering.
2–4 years of experience in a quantitative research, trading, or risk modeling role — preferably in crypto, DeFi, traditional finance, or fintech.
Strong proficiency in Python for quantitative research (e.g. pandas, numpy, scipy, statsmodels, plotly, etc.).
Experience developing and validating models for financial forecasting, portfolio optimization, or risk simulation.
Familiarity with techniques like Monte Carlo simulations, timeseries modeling, and statistical backtesting.
Solid understanding of DeFi primitives (e.g. AMMs, lendingborrowing, stablecoins, LSTs, vaults, yield farming).
Research and design algorithmic yield strategies for stablecoin and crypto vaults, targeting riskadjusted yield optimization through leverage, protocol stacking, and dynamic rebalancing.
Quantitatively assess protocolspecific and systemic risks, including smart contract vulnerabilities, liquidity depth, slippage, oracle dependencies, and market volatility impacts across integrated DeFi protocols
Develop probabilistic and scenariobased models to quantify tail risks, VaR, and protocol failure impact; implement Monte Carlo simulations and agentbased modeling to evaluate strategy robustness across historical and synthetic conditions.
Perform stress tests based on extreme market events, flash loan attacks, and stablecoin depegs to validate strategy durability.
Work closely with smart contract and backend engineers to productionize models, automate rebalancing logic, and integrate risk controls directly into vault infrastructure. Ensure strategy logic is safely and efficiently deployed onchain.
Bachelor’s or Master’s degree in a quantitative field such as Mathematics, Statistics, Physics, Computer Science, Engineering, or Financial Engineering.
2–4 years of experience in a quantitative research, trading, or risk modeling role — preferably in crypto, DeFi, traditional finance, or fintech.
Strong proficiency in Python for quantitative research (e.g. pandas, numpy, scipy, statsmodels, plotly, etc.).
Experience developing and validating models for financial forecasting, portfolio optimization, or risk simulation.
Familiarity with techniques like Monte Carlo simulations, timeseries modeling, and statistical backtesting.
Solid understanding of DeFi primitives (e.g. AMMs, lendingborrowing, stablecoins, LSTs, vaults, yield farming).
You have 🤓
Required profile
Experience
Other Skills
- Teamwork
- Communication
- Problem Solving
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