Описание

Build simulation frameworks to stress test onchain strategies under adverse conditions: depegs, oracle failures, liquidity crunches, cascading liquidations
Model concentration risk, counterparty exposure, and correlation dynamics across the portfolio
Analyse historical onchain data to validate risk assumptions and calibrate model parameters
Produce quantitative risk reports that inform vault construction and rebalancing decisions
Model and backtest baskets of AMM positions: LP construction, fee optimisation, impermanent loss dynamics, and rebalancing strategies for concentrated and full-range liquidity
Work with live protocols and real capital (Morpho, Gearbox, Aave, Uniswap, Balancer)

Bachelor's degree (graduate or recent graduate) in economics & finance, natural sciences, mathematics/statistics, or another quantitative discipline
Analytical and critical thinker with a research mindset; self-starter and autodidact
Programming experience (e.g. Python, NumPy, SciPy, pandas) is a plus
Ability to translate complex systems into tractable models and reason about where the model breaks
Comfortable with probability, stochastic processes, and statistical inference
Knowledge of financial instruments (e.g. options, perpetual trading)
Interest in DeFi and onchain markets; familiarity with AMM mechanics (Uniswap v3/v4, concentrated liquidity) is a strong plus; prior DeFi exposure not required if quantitative foundation is strong

Quantitative Research Graduate — Risk Modelling