Quantitative Developer (C++)

About the role

Tower Research Capital is a leading quantitative trading firm founded in 1998. Tower has built its business on a high-performance platform and independent trading teams. We have a 25+ year track record of innovation and a reputation for discovering unique market opportunities.

Tower is home to some of the world’s best systematic trading and engineering talent. We empower portfolio managers to build their teams and strategies independently while providing the economies of scale that come from a large, global organization.

Engineers thrive at Tower while developing electronic trading infrastructure at a world class level. Our engineers solve challenging problems in the realms of low-latency programming, FPGA technology, hardware acceleration and machine learning. Our ongoing investment in top engineering talent and technology ensures our platform remains unmatched in terms of functionality, scalability and performance.

At Tower, every employee plays a role in our success. Our Business Support teams are essential to building and maintaining the platform that powers everything we do — combining market access, data, compute, and research infrastructure with risk management, compliance, and a full suite of business services. Our Business Support teams enable our trading and engineering teams to perform at their best.

At Tower, employees will find a stimulating, results-oriented environment where highly intelligent and motivated colleagues inspire each other to reach their greatest potential.

You will be working for a successful MFT trading team, helping to enhance existing capabilities and increase robustness of live trading.

Responsibilities

- Designing and implementing a low latency high-frequency trading platform

- Assisting in the development of a tick by tick backtesting research platform

- Assisting in development and optimizing large-scale parallel computation problems that requires large quantities of data shared across resources

- Optimizing the computational efficiency of existing machine learning based algorithms to drive higher performance and faster learning rates

- Developing systems, interfaces and tools to historical market data and trading simulations that increase research productivity

- Creating tools to analyze data and generate insights that research decisions are based on

Qualifications

- 1-5 years of practical experience with C++ and 1-2 years of meaningful experience with Python

- A strong background in data structures, algorithms, and object-oriented programming

- Demonstrated academic excellence

- Strong working knowledge of Linux, and some SQL knowledge

- Brilliant detail oriented problem-solving abilities

- Passion for innovation and building systems from the ground up

- A self-starter attitude with the ability to work independently and own problems