Quantitative Risk Analyst

About

Particula is the leading rating provider for digital assets, aiming to make the market more accessible, secure, and transparent for institutional investors. They support issuers, trading facilities, banks, and asset managers in creating trust, minimizing risks, and allocating capital effectively. Particula is shaping the future of the financial world with its proprietary risk ratings (PDARF) and the Particula Digital Asset Risk Passport (PDARP).

Responsibilities

• Risk Modelling & Quantitative Research: Design and implement stress testing frameworks, develop and backtest predictive models using historical data, run Monte Carlo simulations and scenario analyses, and conduct time series analysis.
• Crypto-Backed Lending & Collateral Risk: Build quantitative assessment frameworks for crypto-backed loan products (ETH, SOL, BTC collateral), model liquidation risk, collateral volatility, and LTV dynamics, and support methodology development for collateral health monitoring.
• Real-World Asset (RWA) Vault Assessment: Develop quantitative approaches to evaluate RWA vaults, contribute to RWA methodology, and integrate RWA risk factors into the broader PDARF framework.
• Research, Publications & Thought Leadership: Produce in-depth quantitative research for external publication, translate complex modeling outputs into clear insights, and represent Particula's expertise through white papers and industry commentary.
• Protocol & Smart Contract Risk Quantification: Quantify risks in DeFi protocol mechanics and build scoring models incorporating on-chain data.
• Market & Liquidity Risk Monitoring: Develop risk dashboards and alert systems for market risk indicators and monitor cross-asset correlations.
• Rating Model Validation & Calibration: Independently validate and back-test risk models, and calibrate rating thresholds and weighting schemes using empirical data.
• Data Infrastructure & Tooling: Build robust analytical pipelines using on-chain and off-chain data sources and contribute to the development of internal quantitative tooling.

Requirements

• Strong foundation in quantitative finance, statistics, or financial engineering.
• Hands-on experience with Python (pandas, NumPy, SciPy, statsmodels) and/or R.
• Familiarity with DeFi mechanisms, tokenomics, and crypto market microstructure.
• Experience with credit risk, collateral modeling, or structured products is a strong plus.
• Excellent written communication skills, capable of authoring publication-ready research.
• Self-driven, intellectually curious, and comfortable operating in a fast-moving environment.

Benefits: Team offsites in exciting locations, flexible working hours, remote work, exciting product in a dynamic market, values-based start-up culture, opportunities for development and networking, flat hierarchy, cash salary plus potential share options.
Location: Remote work.