量化研究员 - 定价模型
Quantitative Researcher - Pricing Model
职位概述
我们正在寻找一名量化分析师/研究员，负责评估、测试并优化我们在加密货币和股权代币上的普通欧式永续合约和期权的定价模型。您将对模型假设进行压力测试，评估极端市场条件下的风险，并从零开始构建新模型。该职位需要在原始波动率定价方面有深入的专业知识，有验证模型的实际经验，并具备从技术研究到生产级量化模型的底层逻辑转化能力。
主要职责
模型开发与优化
- 提升现有模型：测试、基准测试并改进当前的普通欧式永续合约和期权（加密货币和股权代币）定价模型。
- 从零构建模型：设计并原型化新的衍生品工具和代币化结构的数学模型。
- 测试核心假设：深入审计、挑战并基于实时24/7市场数据对模型的底层假设进行实证测试。
模型风险与验证
- 验证与治理：执行端到端模型验证，识别边缘情况、结构性限制和故障点。
- 风险与压力测试：在极端市场情景和尾部风险事件中评估模型表现、希腊值（delta、gamma、vega）和流动性暴露。
量化研究与波动率
- 波动率分析：校准和维护原始波动率定价、隐含波动率曲面、偏斜/微笑动态以及资金费率模型。
- 研究实现：阅读、批判并实现前沿的技术/学术研究论文，以解决复杂的量化问题。
要求
- 衍生品与波动率专长：在衍生品定价（期权、永续合约）、原始波动率建模和曲面校准方面有实际操作经验。
- ● 模型验证背景：在量化金融或交易环境中具有模型风险、回测和压力测试的扎实记录。
- ● 底层逻辑思维：能够从底层逻辑拆解加密货币市场机制，而不是严格依赖传统金融（TradFi）的假设。
- ● 研究能力：能够快速理解并编写来自技术研究论文的复杂公式。
- ● 技术技能：在Python（NumPy、SciPy、Pandas）或C++方面有高级熟练度，用于量化原型开发和分析。
- ● 教育背景：金融工程、量化金融、数学、物理或相关领域的硕士或博士学位。
- ● 领域知识：对加密货币市场有深入了解
查看英文原文
Role Overview
We are looking for a Quantitative Analyst / Researcher to evaluate, test, and enhance our pricing models for plain vanilla perpetual swaps and options across crypto and equity tokens. You will stress-test model assumptions, evaluate risk under extreme market regimes, and build novel models from scratch. This role requires deep expertise in raw volatility pricing, proven model validation experience, and a first-principles approach to translating technical research into production-grade quantitative models.
Key Responsibilities
Model Development & Optimization
- Enhance Existing Models: Test, benchmark, and improve current pricing models for plain vanilla perps and options (crypto & equity tokens).
- Build from Scratch: Design and prototype novel mathematical models for new derivative instruments and tokenized structures.
- Test Core Assumptions: Deeply audit, challenge, and empirically test underlying model assumptions against live 24/7 market data.
Model Risk & Validation
- Validation & Governance: Perform end-to-end model validation, identifying edge cases, structural limitations, and failure points.
- Risk & Stress Testing: Evaluate model performance, greeks (delta, gamma, vega), and liquidity exposure under extreme market scenarios and tail-risk events.
Quantitative Research & Volatility
- Volatility Analytics: Calibrate and maintain raw volatility pricing, implied volatility surfaces, skew/smile dynamics, and funding rate models.
- Research Implementation: Read, critique, and implement cutting-edge technical/academic research papers to solve complex quantitative problems.
Requirements
- Derivatives & Volatility Expertise: Hands-on experience with derivatives pricing (options, perps), raw volatility modeling, and surface calibration.
- ● Model Validation Background: Strong track record in model risk, backtesting, and stress testing within quantitative finance or trading environments.
- ● First-Principles Mindset: Ability to deconstruct crypto market mechanics from first principles rather than relying strictly on legacy TradFi assumptions.
- ● Research Capability: Ability to quickly digest and code complex formulas from technical research papers.
- ● Technical Skills: Advanced proficiency in Python (NumPy, SciPy, Pandas) or C++ for quantitative prototyping and analysis. ● Education: Master’s or Ph.D. in Financial Engineering, Quantitative Finance, Mathematics, Physics, or a related field.
- ● Domain Knowledge: Strong understanding of crypto market microstructure, funding rates, and tokenized equity/RWA assets.
Benefits
What We Offer
- Collaborative remote work environment that allows you to have a work life balance.
- ● Growth framework that drives fast, continuous improvement
- ● Opportunity to learn and collaborate with the leadership team.
- ● Exciting team offsites and employee engagement activities.
- ● Competitive compensation and exposure to closely with teams.
Originally posted on Himalayas