Develops strategic research and quantitative trading systems for multiple frequencies and products. The intern will help design and build technology supporting research and live trading, using Python or C++ and tools such as Linux, Git, Conda, and CI processes. Work may involve cloud platforms, databases, distributed or streaming computing, data science, and machine learning. Candidates should demonstrate quantitative skills, communication, attention to detail, ownership, teamwork, and ethical judgment.
About Cubist
Cubist Systematic Strategies, an affiliate of Point72, is one of the world’s premier investment firms. The firm deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures, and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources.
Job Description
The Central Research Technology team, which builds strategic solutions for research and live trading of quantitative strategies across multiple frequencies and products, is seeking a highly talented intern to work with the team in January. This is a unique opportunity to help design and build the next generation of research and quant trading systems for Cubist.
Desirable Candidates
- Undergraduate or graduate candidates in computer science or engineering
- Significant experience in Python and/or C++
- Interest in open source research tools for data science and machine learning
- Basic knowledge of linux, git, conda, and CI processes
- Knowledge of cloud, databases and distributed or streaming compute is a plus
- Reasonable quantitative and statistical skills
- Experience with Finance preferred
- Clear, concise, and proactive communicator
- Detail oriented and quick learner in a fast-paced environment
- Team player with strong pride of ownership
- Commitment to the highest ethical standards
Point72 New York, New York, USA Office
55 Hudson Yards , New York, United States, 10001
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