Skip to main content

Tower Research Capital

Quantitative Developer Intern - Summer 2027

New York, ChicagointernAdded 1 month ago

About this role

Tower Research Capital seeks a Quantitative Developer Intern to build and optimize high-performance trading systems and infrastructure. You'll work alongside traders and researchers to develop low-latency systems, analyze market data, and operate sophisticated trading strategies in a fast-paced quantitative trading environment.

What you'll do

  • Design and optimize low-latency trading systems and high-throughput training infrastructure
  • Collaborate with traders and researchers to understand strategy requirements
  • Build data analysis tools to identify market patterns
  • Conduct post-trade analysis and market observations
  • Develop and calibrate exchange simulators
  • Operate high-frequency trading strategies

What they're looking for

  • C++ or Python programming
  • Low-latency systems design
  • Linux/Unix proficiency
  • Problem-solving and debugging
  • Data analysis and pattern recognition
  • Machine learning (preferred)
  • Financial market knowledge
  • Communication and teamwork

Benefits

  • Competitive compensation ($3,500-5,700 weekly base)
  • Housing accommodation provided
  • Free meals daily (breakfast, lunch, snacks)
  • Networking events and social activities
  • Mentorship from senior leaders and alumni
  • Collaborative, ego-free work culture
Apply on the employer's site

Opens the official application on the employer’s site. No login required.

Tower Research Capital

Tower Research Capital builds high-performance quantitative trading systems and infrastructure, serving traders and researchers with low-latency platforms for market data, strategy execution, and order management. The company is hiring software engineers, quantitative developers, and infrastructure specialists to design scalable systems, optimize trading platforms, and enhance development tooling.

View all jobs at Tower Research Capital

Likely interview questions

  • Walk us through a time you optimized code for performance—what was your approach and what improvements did you achieve?
  • How would you approach designing a low-latency system, and what factors would you prioritize?