About this role
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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.