Posted 5mo ago

Head of Quantitative Modelling & Research

@ SD Guthrie
Singapore, Singapore
OnsiteFull Time
Responsibilities:Developing infrastructure, Calibrating models, Leading implementation
Requirements Summary:PhD or Master’s in a quantitative field; 10+ years in derivatives, market making, or related research.
Technical Tools Mentioned:Python, C++, MATLAB, R
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Job Description

We value our people and encourage everyone to grow professionally. If you think this opportunity is right for you, we encourage you to apply!

Job Description:

Roles & Responsibilities

Options Market Making, Calibration & Smile Modeling 

  • Develop and own the quantitative infrastructure for quoting and risk managing vanilla and exotic options, including: 

  • Real-time volatility surfaces 

  • Greeks engines 

  • Market-making and execution algorithms 

  • Lead implementation of arbitrage-free volatility smile and skew models, including: 

  • Smile parameterisation techniques: e.g. SVI, SABR, and Fengler’s arbitrage-free smoothing approaches 

  • Local volatility models: Dupire local volatility for smile-consistent pricing and delta-hedging 

  • Mixed local/stochastic volatility models: for capturing dynamic skew behaviour under stressed conditions 

  • Build robust model calibration pipelines to liquid market instruments (e.g. vanilla options, forwards, futures) ensuring: 

  • Fast convergence 

  • Numerical stability 

  • No calendar, butterfly, or vertical spread arbitrage 

  • Extend volatility modelling to handle long-dated exotic derivatives: 

  • American barriers, Asian accumulators, spread options, TARFs 

  • Currency-denominated option structures with quanto and correlation features 

 

Term Structure & Correlation Modelling 

  • Develop multi-factor forward curve models for commodities and currencies: 

  • Gabillon Two-Factor Model for capturing commodity forward curve dynamics 

  • Schwartz-Smith or CIR++ extensions for interest rate and inflation-linked exposure 

  • Model and estimate cross-asset correlations, particularly between: 

  • Commodities (oil, palm, soy, energy, etc.) 

  • Currencies (USD, CNY, MYR, INR, etc.) 

  • Freight and storage costs 

  • Integrate correlation modeling into: 

  • Structured products 

  • Portfolio VaR / CVaR frameworks 

  • Basis risk hedging strategies 

 

Real Assets & Physical Optionality 

  • Build stochastic optimization and valuation frameworks for: 

  • Crushing/refining spreads (e.g. soybean crush, palm kernel crush) 

  • Storage and logistics assets as American swing options 

  • Real-time asset monetization tools using Monte Carlo simulation, real options valuation, and basis path modeling 

  • Incorporate physical constraints (capacity, delivery time, transport) into derivatives-driven optimization 

Ideal Candidate 

  •  PhD or Master’s in a quantitative field (Mathematics, Financial Engineering, Physics, Computer Science) 

  • Background in commodities markets (energy, agri, metals) 

  • Experience building physical-real optionality models 

  • Exposure to algorithmic quoting engines and real-time market data feeds 

  • Understanding of machine learning techniques for market regime switching or signal generation 

  • 10+ years of experience in: 

  • Quantitative research for derivatives trading or market making 

  • Building volatility surfaces, smile models, and calibration tools 

  • Exotic option pricing in commodity, currency, or hybrid markets 

 

To apply, please submit your resume and cover letter outlining your interest for this role.