Tower Research Capital
New York, NY
Quantitative Trader Intern, PhD
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Apply to Quantitative Trader Intern, PhD at Tower Research CapitalJob details
- Location
- New York, NY
- Work type
- Onsite
- Compensation
- $182,000 - $296,400/yr
- Visa
- Sponsorship available
- Posted
- 1 week ago
- Apply on
- boards.greenhouse.io
About this role
Tower Research Capital is a leading quantitative trading firm founded in 1998. They are seeking a Quantitative Trader Intern to design and implement high-frequency trading algorithms while collaborating with mentors to enhance trading strategies.
What you'll do:
- Designing, implementing, and deploying high-frequency trading algorithms
- Working with a dedicated mentor to research and enhance existing trading strategies
- Exploring trading ideas by analyzing market data and market microstructure for patterns
- Creating tools to analyze data for patterns
- Contributing to libraries of analytical computations to support market data analysis and trading
- Developing, augmenting, and calibrating exchange simulators
What they're looking for:
- Availability for 4-6 months or 10-week summer term
- PhD student focusing on mathematics, statistics, physics, electrical engineering, computer science, economics, or related fields
- A strong background in C++, R, Python, or an object-oriented programming language
- Strong problem-solving abilities
- A passion for new technologies and ideas
- The ability to manage multiple tasks in a fast-paced environment
- Strong communication skills
- Interest in financial markets
- Past industry experience
- Experience with machine learning
Benefits:
- Free breakfast, lunch, and snacks daily
- Exciting networking and social events (e.g. Broadway shows, escape rooms, cooking classes)
- Opportunities to learn from senior management across the firm
- Mentors from your alma mater and other top institutions
- Competitive compensation package
- Our open concept workplace, casual dress code, and well-stocked kitchens reflect the value we place on a friendly, collaborative environment where everyone is respected, and great ideas win
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