Quantitative Trading Intern — Build High-Frequency Algorithms

Aplaro Ltd

New York (NY)

On-site

USD 136,500 - 227,500

Full time

14 days+

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Benefits offered by this job

Competitive compensation package
Free breakfast, lunch, and snacks
Networking and social events
Mentorship from senior management
Collaborative and welcoming culture

Job summary

Tower Research Capital is conducting an internship in New York focused on designing and deploying high-frequency trading algorithms. You will work with a mentor to research and enhance trading strategies while exploring market data and microstructure to identify patterns.

The role emphasizes strong programming in C++, R, or Python, problem-solving, multitasking, and effective communication, with interest in financial markets and exposure to financial technology.

Qualifications

  • Availability for 4-6 months or 10-week summer term.
  • PhD student in mathematics, statistics, physics, electrical engineering, computer science, economics, or related fields.
  • Strong background in C++, R, Python or an object-oriented language.
  • Strong problem-solving abilities.
  • Passion for new technologies and ideas.
  • Ability to manage multiple tasks in a fast-paced environment.
  • Strong communication skills.
  • Interest in financial markets.

Responsibilities

  • Designing, implementing, and deploying high-frequency trading algorithms.
  • Research and enhance existing trading strategies with a mentor.
  • Analyze market data and market microstructure to identify patterns.
  • Create tools to analyze data for patterns.
  • Contribute to libraries of analytical computations for market data analysis and trading.
  • Develop, augment, and calibrate exchange simulators.

Skills

C++
R
Python
Problem solving
Multitasking
Communication
Finance interest

Job description

Tower Research Capital is conducting an internship in New York focused on designing and deploying high-frequency trading algorithms. You will work with a mentor to research and enhance trading strategies while exploring market data and microstructure to identify patterns.

The role emphasizes strong programming in C++, R, or Python, problem-solving, multitasking, and effective communication, with interest in financial markets and exposure to financial technology.

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