The quant in Risk Management will be engaged in a variety of tasks in risk management and controls. Specific responsibilities: Developing risk management models to measure risks of different businesses and commodity-related transactions. Estimating and calibrating parameters for use in risk models (such as volatilities and correlations of forward prices, mean-reversion rates, etc.). Measuring and monitoring portfolio risks, including develop and implement Value-at-Risk and stress-testing methodologies. Validating key quantitative/analytical models developed by businesses and affiliates of the Group. Developing IT solutions appropriate to handle exotic option valuations and advanced value-at-risk type computations for different commodities and portfolios of deals. Role and Responsibilities: The candidate(s) is motivated by the opportunity to grow in a multi-commodities and multi-talented fast-pace environment and is excited about the quantitative challenges of the cutting-edge commodities supply and trading business. Satisfaction is found working for a leading and fast growing commodity company with one of the most diverse mixes of commodities/ geographies in the world. The candidate will rise to the complex tasks presented by constant deal flow and have the tenacity to follow a set of complex controls that insure smooth deal execution and risk management. The specific projects can include: - Model the stochastic properties of commodities foward and spot prices. - Determine the estimation procedure of the model parameters and determine statistical significance of the results. - Develop volatility and correlation models that capture observed price behavior while affording analytical tractability and practicality for use in valuation and risk models. - Estimate commodities volatilities of forward contracts at illiquid locations. Calibrate implied volatility curves to available broker quotes. Assess cross-maturity (such as between futures contracts with different delivery months) and cross-commodity correlations (such as between soft commodities and energy commodities) of high quality in order to accurately value physical assets and cross-commodity derivatives. - Implement and enhance Monte Carlo price simulation models and methodologies to balance requirements for model accuracy, speed, and flexibility. - Compute portfolio risk using Value-at-Risk methodologies. - Understand complex portfolios composition and discern and report on portfolio risks. Such portfolios may include a variety of physical assets and financial instruments. - Evaluate the effectiveness of risk models in assessing the risk of the portfolio. Enhance risk computation methodologies. Perform model back-testing and portfolio stress-test analyses. - Assess and report on the effectiveness of hedging strategies and programs. Requirements: - Ability to work as part of a team and independently with multiple risk projects under tight deadlines. - Direct experience with mathematical and computational finance such as options pricing and risk models, implementation of Value-at-Risk methodologies. - Experience/exposure to commodities markets and trading would be a plus. - Programming experience in VBA, C++, MatLab, SQL, relational database. - Hands on experience with Risk system and VaR calculation engines would be a plus. - Advanced degree in Financial Engineering, Mathematical and Computational Finance, Physics, Statistics, Mathematics or other quantitative discipline. - Excellent written and verbal communication skills.