New York, New York, United States
Conduct quantitative analysis and research on components of trade process in quantitative option financial market making system. Perform quantitative analysis of historical and real-time tick-level financial market data and develop latency sensitive forecasts of parameters going into option pricing financial models. Write, test, and deploy production quality (highly reliable, tunable, and scalable) software for automated financial risk management system. Apply statistical and numerical methods to understand and optimize performance of critical financial market trading algorithms.
Requires a Ph.D. Degree in Mathematics, Statistics, Physics, Computer Science, Computer Engineering or Electrical Engineering plus 1 year of experience in a Quantitative Research position or in the alternative Master’s Degree in Mathematics, Statistics, Physics, Computer Science, Computer Engineering or Electrical Engineering plus 3 years of experience in a Quantitative Research position.
Must have experience using the following skills and technologies:
- Principles of mathematical, statistical, and financial modeling;
- Time-series and large datasets analysis;
- Parameters estimation using machine learning techniques;
- Mathematical modeling including analytical derivations and numerical simulations;
- Stochastic processes, perturbation analysis and harmonic analysis;
- Statistical inference and optimization;
- Algorithms and numerical methods, linear algebra and Partial Differential Equation numerical solvers;
- Option pricing theory, analyzing P&L, inventory and risks;
- C++, Python (including numpy, scipy, pandas, linear algebra, and plotting packages), Linux, Bash and version control systems; and
- Knowledge of US stocks, ETFs, indices, futures, VIX futures, and also options traded on these underliers.
Must also pass company’s required skills assessment test.