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