E-Markets Systematic Trading [Multiple Positions Available]
DESCRIPTION:
Duties: Design and implement high-quality systematic risk management models for interest rate products. Analyze client flow patterns to optimize systematic pricing and risk management strategies. Develop and maintain an automatic hedging system for interest rate futures, cash bonds, and bond futures. Conduct data analysis to identify patterns and uncover revenue opportunities. Perform back testing and evaluate pricing, risk management, and execution strategies. Expand and enhance the group's library of modeling, analytics, and automation tools. Review trading performance and make data-driven decisions to improve outcomes. Maintain and upgrade trading software systems and tools to ensure optimal performance. Resolve day-to-day trading issues to ensure smooth and efficient operations.
QUALIFICATIONS:
Minimum education and experience required: Master's degree in Financial Engineering, Mathematics, Statistics, or related field of study plus three (3) years of experience in the job offered or as E-Markets Systematic Trading, Quantitative Researcher, related occupation. The employer will alternatively accept a Bachelor's Degree in Financial Engineering, Mathematics, Statistics, or related field of study plus five (5) years of experience in the job offered or as E-Markets Systematic Trading, Quantitative Researcher, related occupation.
Skills Required: This position requires experience with the following: using Python to analyze interest rate derivatives, including pricing and risk management; constructing and calibrating interest rate curves using techniques including cubic spline interpolation, bootstrapping, and non-parametric curve building; using Python to analyze interest rate market microstructure, including trading mechanisms and liquidity dynamics; developing and implementing relative value trading signals in Python for interest rate products based on time-series analysis; performing risk decomposition of interest rate products and conducting profit and loss (PnL) attribution analysis to evaluate trading performance; using C++ or Java to develop derivatives pricing tools and risk sensitivity analytics tools; using Python to develop real-time risk monitoring tools, data visualization tools, and generate automated analytics reports; using Python to apply statistical methods and machine learning techniques, including multivariate regression, classification, and predictive modeling, to analyze datasets.
Job Location: 270 Park Ave, New York, NY 10017.
Full-Time. Salary: $235,000 - $285,000 per year.