Quantitative Software Engineer (Derivatives Relative Value)
New York, New York, United States
Duties: Design, engineer, implement, maintain, and upgrade sophisticated quantitative analysis and algorithmic trading software systems for financial services firm. Design and engineer quantitative research software, particularly with highly reliable and highly fine-tuned numerical code, and use these tools to analyze large-scale data sets, such as the US-listed options market history data, exchange-traded funds, and other global macro-economic and equity instruments besides financial derivatives on them. Innovate and improve on firm’s proprietary trading software models and algorithms and implement such models/algorithms in terms of extremely high-performance, high-reliability, and highly robust computational software in the Java/C++ or Python language.
Minimum requirements: PhD in Computer Science, Computer Engineering, Applied Mathematics, Statistics, Physics, or a related quantitative field plus knowledge of the required skills listed below.
Alternative minimum requirements: Master’s Degree in Computer Science, Computer Engineering, Applied Mathematics, Statistics, Physics, or a related quantitative field plus 3 years of experience in Quantitative Research positions plus knowledge of the required skills listed below.
Must have knowledge of the following quantitative skills and software technologies:
object-oriented programming, memory/time complexity analysis, and data structure plus numerical analysis and numerical linear algebra;
advanced analytical skills including partial differential equations (PDE), probability theory, and stochastic analysis; scientific computing, algorithm development, and pattern recognition;
building/engineering large-scale, real-time, and distributed software; developing/engineering high-performance, multi-threaded software using several production-level programming languages including Java and C++;
source code version control tools including hg/mercurial and git;
Unix-like operating systems (including Linux) and BASH shell scripting;
Python data analysis language and associated quantitative packages (numpy, scipy, pandas, and statsmodels);
knowledge of the US and global financial markets and pricing of derivatives and other electronically traded products;
designing, implementing, and maintaining algorithmic trading as well as their simulation systems; and
financial portfolio analysis, risk management, and trading market impact research.