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AI Options Volatility Surface Modeling Engineer

Dominic Johansson

Full-time · Job · New_York

About the role

Implied volatility surfaces encode the market's forward-looking uncertainty across strikes and maturities. A well-calibrated vol surface is the foundation for options pricing, delta hedging, risk management, and structured product valuation. An incorrectly modeled surface produces mispricings that compound through an entire options book. We provide quantitative analytics to 30 institutional trading desks and asset managers. Volatility surface modeling is the highest-stakes analytics product we build: errors translate directly to P&L consequences for clients managing multi-billion-dollar options portfolios. Our current approach uses SVI parametrization with standard calibration; clients want better handling of the volatility term structure in low-liquidity expiries and more robust surface construction in crisis regimes when the smile distorts sharply. This is a senior role requiring genuine quant finance depth and ML expertise. You'll design improved surface construction models that handle crisis regimes without arbitrage violations, implement uncertainty quantification on vol estimates, and build the real-time calibration pipeline that runs on live market data. Compensation reflects the expertise required. The role is hybrid — 3 days in NYC for trading desk collaboration.

Responsibilities

  • Design improved volatility surface construction models robust to crisis regime smile distortion
  • Implement arbitrage-free surface interpolation with uncertainty quantification on thin-strike regions
  • Build real-time surface calibration pipeline running on live options market data
  • Develop volatility term structure models improving accuracy in low-liquidity expiries
  • Create surface quality metrics monitoring for arbitrage violations and calibration drift
  • Validate surface models against realized volatility and independent desk pricing

Requirements

  • 7+ years in quantitative finance with options pricing and volatility modeling expertise
  • Deep understanding of stochastic volatility models, smile dynamics, and surface parametrization
  • Strong Python and statistical computing skills with quantitative finance library experience
  • Familiarity with ML applications in derivatives pricing and risk
  • Track record building production quantitative systems for institutional trading clients

Benefits

  • Hybrid: 3 days NYC, 2 days remote
  • Top-of-market compensation for quantitative finance ML expertise
  • Comprehensive benefits package
  • Equity participation
  • Annual performance bonus

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Categories

data science & analytics AI & Machine Learning Engineers

Skills

python pytorch statistics spark sql

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Job Type

Full-time

Level

Senior

Language

English

Salary Range

$200k+ / year

AI Expertise

data science & analytics AI & Machine Learning Engineers

Skills

python pytorch statistics spark sql pandas

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