Quantitative Financial Engineer (TGS)

Under the direction of a Senior Information Technology Officer, the Quantitative Financial Engineer will serve as a member of the Economic Modeling Support Group, and will work on quantitative finance modeling. The successful candidate will be required to implement financial models, advanced econometric methods, and numerical algorithms using several programming languages. In addition, the design and implementation of high power computing solutions may be required for very large or computationally intensive models. The successful candidate will also be expected to provide support and training for the models being developed.

This position requires advanced programming skills and a strong background in quantitative finance, applied mathematics and computer science. The successful candidate should have expert knowledge of arbitrage-based asset pricing, term-structure modeling, credit risk models, bond pricing and risk measures.

This position also requires familiarity with advanced econometric methods and models, including Ordinary Least Squares, Maximum Likelihood, and State-Space models.

The successful candidate should also have a solid understanding of numerical methods such as optimization (unconstrained and constrained), optimal control, dynamic programming, integration, and Monte-Carlo simulation.

Finally, the successful candidate should be proficient in Matlab and either C++ or a .Net language (preferably C#)

Qualifications

The successful candidate should posses a PhD in applied mathematics or finance.

Knowledge

The successful candidate will possess an in-depth, demonstrated knowledge of:

• Derivative pricing, bond pricing and risk analysis, term-structure modeling;
• Value-at-risk (VaR) computation for various types of portfolios;
• Dynamic programming, constrained and unconstrained optimization theory and optimal control;
• Stochastic differential equations, stochastic integration and stochastic calculus;
• Probability theory and Bayesian inference;
• Monte-Carlo simulation of multiple correlated processes, Markov Chain Monte Carlo simulation, including Gibbs sampler and Metropolis-Hastings algorithm;
• Partial differential equations, ordinary differential equations and numerical integration;
• Stochastic dynamic programming;
• Linear algebra;
• Advanced econometrics (including but not limited to OLS, maximum likelihood, instrumental variables, and GMM estimation);
• Object-oriented programming and data structures;
• Personal computer architecture and memory organization, distributed and parallel computing;
• Several high level programming languages specific to modeling packages available in the Fund such as: Matlab, Mathematica, EViews, Fame, Gauss, TROLL;
• C++ or C# programming; and
• Microsoft Office add-in development using .Net.

Ability

• Ability to follow up current academic research on quantitative finance, computational economics, statistics, and econometrics;
• Ability to train or teach others on highly specialized topics;
• Ability to find innovative solutions to unusual problems; and
• Ability to write and communicate effectively with peers, users and management.

This position will be offered as a one-year contract initially, with the possibility of further extensions.

	Quantitative Financial Engineer (TGS)