SD Guthrie

Head of Quantitative Modelling & Research

SD Guthrie

SingaporeFull timePosted Aug 3, 2026

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.