Job Description

Position Summary

Develop and implement industry leading valuation models, providing direct support for complex trade floor Risk Systems and operations. Applies knowledge of standard quantitative/computational finance methods to energy commodity Risk System pricing and valuation spaces. Demanding internal customers and fast-paced trade floor operations require the ability to efficiently and effectively solve complex quantitative problems.

Essential Responsibilities

Review and quickly understand commercial terms of standard and structured energy commodity contracts.
Identify and validate pricing visible parameters and estimate illiquid pricing parameters.
Develop, implement and standardize pricing and valuation models to estimate risk, position and value or real energy options.
Leverage existing quantitative skills, knowledge of energy commodity markets and structured products to solve quantitative problems.
Develop and implement portfolio market risk distribution estimation methods.
Benchmark, test and document transaction pricing models and system valuation models.
Ensure model development can be leveraged across the trade floor by commercial and control personnel.
Coordinate with Risk Operations/other groups to implement system valuation models and methods in a robust, accurate, and timely manner.

Minimum Requirements

Master's Degree in a numerate discipline, such as computer science, mathematics, engineering, physics or similar quantitative field.
Minimum 2 years of deal structuring, risk management, and/or coding experience.
Understanding of pricing and valuation of complex, structured products in the energy commodity markets.
Demonstrated ability to use statistical methods to model and explain energy market and contract risk characteristics.
Knowledge of standard quantitative/computational finance methods and ability to apply them to pricing energy commodity market real options and structured products.
Experience with parameter estimation, both using large data sets as well as when faced with sparse and illiquid market data.
Programming skills for data analytics and model implementation, including Python; R and C++ desirable.
Knowledge of Trading Risk Systems; Triplepoint CXL, SAS, Morningstar Curve Manager and IBM ESB preferred.
Ability to communicate effectively with demanding customers on a fast paced energy trade floor.