Quantitative Developer Intern

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.

Please note, this internship opportunity is open to those who are available from February 2027 for six months.

Responsibilities

• Iterating quickly with on-site quantitative researchers on the research processes in order to improve the desk's quantitative trading strategies P&L

• Developing Python tools used in trading strategies research

• Improving the existing simulation/backtest framework

• Help global research team on EMEA-related research through various communication channels

Qualifications

• Currently in the final year of a Master’s degree in Computer Science, Engineering, Applied Math, or a related field

• Strong interest in quantitative finance and software development

• Solid foundation in Python programming and exposure to libraries such as NumPy, Pandas, or Polars through coursework or personal projects

• Demonstrated curiosity, problem-solving ability, and a desire to grow in a fast-paced, collaborative, and intellectually demanding environment

• Good communication skills and willingness to work as part of a distributed team