Role at a glance
- Salary
- Not Disclosed
- Location
- Paris Paris, Paris, France
- Employment
- Internship
- Education
- Currently in the final year of a Master’s degree in Computer Science, Engineering, Applied Math, or a related field
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Role Summary
The Quantitative Developer Intern works with quantitative researchers to support research into quantitative trading strategies. The role develops Python research tools and improves the simulation and backtest framework.
What You'll Do
- Iterate with on-site quantitative researchers on research processes to improve the desk’s quantitative trading strategies P&L.
- Develop Python tools used in trading strategy research.
- Improve the existing simulation/backtest framework.
- Support the global research team on EMEA-related research through various communication channels.
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
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 Python foundation and exposure to NumPy, Pandas, or Polars through coursework or personal projects. The posting also calls for curiosity, problem-solving ability, communication skills, and willingness to work on a distributed team, along with interest in learning about large-scale systems, workflow orchestration, and production-grade software engineering practices.
Required
- 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...
- Good communication skills and willingness to work as part of a distributed team
- Interest in learning about large-scale systems, workflow orchestration, and production-grade software engineering practices
Preferred
- Exposure to C++ and/or scripting languages (e.g., Bash) is a plus
Original job description
Content provided by the employer
Original job description
Content provided by the employer
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
- Exposure to C++ and/or scripting languages (e.g., Bash) is a plus
- Interest in learning about large-scale systems, workflow orchestration, and production-grade software engineering practices
Benefits
- Competitive compensation package
- Free breakfast, lunch, and snacks daily
- Exciting networking and social events
- Opportunities to learn from senior management across the firm
- Mentors from your alma mater and other top institutions
Tower Research Capital is an equal opportunity employer.
About the company
Tower Research Capital
Large Enterprise
Tower Research Capital is a global financial services firm specializing in quantitative trading and technology-driven market making. Founded in 1998, the company leverages advanced mathematical models and cutting-edge technology to analyze market trends and execute trades across various asset classes. With a focus on innovation and efficiency, Tower Research Capital is committed to providing liquidity and enhancing market stability, often operating at the intersection of finance and technology. The firm fosters a collaborative environment that encourages talent development and embraces a diverse workforce, making it an ideal setting for aspiring finance professionals and tech enthusiasts alike.