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永续合约量化风控策略专家 (CEX/DEX Quant Risk - Perps Strategy)

L

Lorenzo Protocol

10 - 15K USD
Full-time
Remote
维持保证金/MMR标记价格 / Mark Price阶梯清算 / Tiered Liquidation自动减仓 / ADL资金费率 / Funding Rate压力测试 / Stress Testing保险基金 / Insurance Fund Black Swan

Key words: 维持保证金 / Maintenance Margin (MMR)、标记价格 / Mark Price (Anti-Manipulation)、阶梯清算 / Tiered Liquidation、自动减仓 / ADL (Auto-Deleveraging)、资金费率 / Funding Rate (Convergence)、压力测试 / Stress Testing (Black Swan)、保险基金 / Insurance Fund (Solvency)

职位描述:

1. 清算逻辑设计(核心防穿仓):

  • 分级清算(Liquidation Tiers):设计并优化阶梯维持保证金(MMR)模型。根据持仓规模动态调整清算阈值,确保大额头寸在穿仓前有足够的流动性深度进行减仓。
  • 清算执行算法:定义清算单如何进入撮合引擎(如:强制减仓、立即成交或取消订单、接管仓位),并优化清算单的撮合优先级,防止清算延时。

2. 标记价格与反作弊(输入源防线):

  • 指数算法优化:构建多源聚合的永续合约标记价格(Mark Price)算法,设计异常价格剔除(Median/Moving Average)机制,防御针对预言机的价格操纵(Oracle Attack)。
  • 风控参数管理:实时根据市场流动性,动态调整资金费率上限(Funding Cap)和价格偏离限价(Price Bands)。

3. 极端风险对冲(最后防线):

  • 保险基金建模:建立保险基金(Insurance Fund)消耗模型,通过历史回测(Backtesting)和压力测试(Stress Test),确保准备金足以覆盖极端穿仓坏账。
  • ADL 机制管理:优化自动减仓(ADL)触发逻辑及排序算法,确保在极端流动性枯竭时,能以最小的副作用维持平台整体偿付能力。

4. 跨部门协作(架构落地):

  • 业务逻辑转译:将数学风控模型转化为高性能开发逻辑,深度参与撮合引擎中风控模块(Risk Module)的架构评审,确保规则在微秒级内准确执行。

职位要求:

  • 数学、金融工程、计算机科学或统计学硕士/博士。3年以上 Top 5 交易所、顶级 HFT(如 Jump/Jane Street)或清算所(CCP)的衍生品风控经验。
  • 必须精通全仓/逐仓、资金费率、标记价格、未实现盈亏结算逻辑。
  • 精通 Python (Pandas/NumPy)SQL。能独立对千万级 Tick 数据进行回测。
  • 理解内存撮合引擎的工作原理,能评估风控逻辑对系统延迟(Latency)的影响。


加分项:

有设计过多资产保证金(Multi-Assets Margin)或统一账户(Unified Account)系统经验者优先。


Job Title: Senior Quant Risk Strategist (CEX/DEX Perps & Derivatives)

Location: Global/Remote

Department: Risk Management

Role Purpose:

As the "Chief Architect of Financial Defense," your mission is to design, implement, and optimize the automated liquidation and risk control frameworks for Perpetual Contracts (Perps). You will ensure the platform remains solvent and the Insurance Fund is protected, even during extreme market volatility (Black Swan events), while maintaining a competitive leverage environment for users.

Job Responsibilities:

  1. Liquidation Engine & Bankruptcy Defense
  • Tiered Liquidation Design: Develop and refine Maintenance Margin Ratio (MMR) and Initial Margin (IM) tiers based on position size and market liquidity to ensure ample buffer before bankruptcy.
  • Execution Algorithms: Optimize how liquidation orders enter the Matching Engine (e.g., IOC orders, split-clearing, or system takeover) to minimize slippage and avoid "Liquidation Cascades."
  • Anti-Clawback Management: Manage the Insurance Fund health and design the Auto-Deleveraging (ADL) ranking logic to handle residual bad debt in extreme liquidity crunches.
  1. Index & Mark Price Integrity
  • Oracle & Index Robustness: Design multi-source Index Price aggregation algorithms with outlier detection (e.g., median filtering) to defend against price manipulation and flash crashes.
  • Mark Price Optimization: Maintain the Mark Price mechanism to prevent unnecessary liquidations caused by low-depth market volatility while ensuring it tracks the Index Price closely via Funding Rates.
  1. Quantitative Stress Testing & Backtesting
  • Scenario Analysis: Conduct rigorous Stress Tests (e.g., simulating -50% price drops within minutes) to estimate Expected Shortfall (ES) and Insurance Fund depletion rates.
  • Parameter Backtesting: Use historical Tick data to simulate how changes in Leverage or Funding Rate Caps impact both user experience and platform risk exposure.
  1. Risk-Engine Architecture Collaboration
  • Logic Translation: Act as the bridge between financial math and engineering. Translate complex risk formulas into high-performance logic for the Matching Engine developers.
  • Latency-Aware Risk Control: Ensure that risk checks (Margin/PNL calculations) are optimized for low-latency execution within the Order Management System (OMS).

Job Requirements:

  • Master’s or PhD in Mathematics, Financial Engineering, Physics, or Computer Science.
  • 3+ years of core experience in a CEX/DEX, HFT firm (e.g., Jump, Jane Street), or Central Counterparty (CCP).
  • Profound understanding of Perpetual Swaps (Perps), including Funding Rates, Cross/Isolated Margin, and PNL settlement.
  • Expertise in Python (Pandas, SciPy, Statsmodels) for modeling and SQL for large-scale data extraction.
  • Familiar with the architecture of Matching Engines and how risk modules interact with order flows.
  • Solid grasp of derivative pricing, Greeks, VaR/CVaR, and market microstructure.