Sign up free to see how well your resume matches this role.
DESCRIPTION:
Duties: Research and development of derivatives margin models including market stress calibration, historical backtesting, system design, and implementation. Drive client engagement and feedback throughout model development lifecycle and provide on-going support after model deployment. Implement mathematical models ensuring seamless integration with credit risk management and margin calculation platforms. Prepare comprehensive documentation and perform rigorous testing of quantitative models to support internal model validation processes. Serve as a subject-matter expert in regulatory meetings related to quantitative modeling for counterparty credit risk and initial margin calculations. Drive the end-to-end model development lifecycle, including source code control, release testing, and model deployment.
QUALIFICATIONS:
Minimum education and experience required: Master's degree in Mathematics of Finance, Quantitative Financial Modeling, Computational Finance, Mathematics, Statistics, Physics, or related field of study plus 2 years of experience in the job offered or as Quantitative Research or related occupation.
Skills Required: This position requires experience with the following: Using mathematical models including No-arbitrage pricing theory, stochastic calculus, probability theory, reduced-form intensity model, Monte Carlo simulation methods, and continuous time stochastic processes to quantify counterparty credit risk of Credit Valuation Adjustment (CVA), Funding Valuation Adjustment (FVA), Potential Future Exposure (PFE), and capital and stressed exposures; building portfolio and trade-level margin models for financial derivatives including swaps, options and exotic, path-dependent derivatives; utilizing Value-at-Risk (VaR) analysis for exposure and margin model backtesting; Implementing CVA, FVA, PFE, regulatory exposure and margin models in C++ and Python utilizing profiling tools including Valgrind, Intel VTune and Visual Studio Profiler to identify performance bottleneck and applying parallel and GPU computing techniques including CUDA to optimize performance.
Job Location: 270 Park Avenue, New York, NY 10017.
Full-Time. Salary: $205,000 - $285,000 per year.
