QUANTITATIVE SOFTWARE ENGINEER
New York, New York, United States
Duties: Design, engineer, implement, and maintain quantitative software tools and technologies used to analyze predictive models, investments, and financial markets. Devise and develop/engineer high-performance data processing software applications that can handle streaming real-time data processing and batch data processing functions. Design and engineer graphical user interface and quantitative data visualizations to display results of analysis and surface insights. Ensure the correctness of analysis and propose improvements to methodologies using understanding of the business context, quantitative statistical skills, and finance domain knowledge. Collaborate with business users (e.g. researchers, portfolio managers, traders) to gather software requirements and devise and implement quantitative software technology solutions that address the requirements at hand. Document requirements, engineering design, and operation procedures. Collaborate with other Engineering teams to evaluate and pilot quantitative software technologies.
Minimum education required: Bachelor’s Degree in Computer Science, Computer Engineering, Materials Science and Engineering, Applied Mathematics, or Physics.
Minimum experience required: 18 months of experience in the job offered or in a Quantitative Strategist position.
Skills required: Must have knowledge of the following quantitative/computing skills and software technologies:
- Back-end development in Java, C++, or Scala;
- Linux/Unix operating system;
- Python or Bash scripting languages;
- Computer Architecture, Operating Systems, Algorithms, and Data Structures;
- Working on large-scale programming projects with over 20k lines of code;
- Fundamental mathematics, including statistics and linear algebra;
- Numerical programming skills utilizing statistical or scientific computing libraries and technologies such as pandas, numpy/scipy, and scikit-learn in Python, Boost in C++, and Apache Spark; and
- Developing large-scale distributed systems for risk and P&L (profit and loss) calculation.