Quantitative Researcher
New York, Chicago
Point72
We invest in Discretionary Long/Short, Macro, and Systematic strategies. We’re inventing the future of finance by revolutionizing how we develop our people and how we use data to shape our thinking. Join our team to innovate, experiment, and be...ABOUT CUBIST
Cubist Systematic Strategies 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.
RESPONSIBILITIES
- Perform rigorous applied research to discover systematic anomalies in equities markets
- Present actionable trading ideas and enhance existing strategies
- Identify short term opportunities in the high frequency/intraday space
- Participate in end-to-end development (i.e. data orchestration, alpha idea generation, simulation, strategy implementation, and performance evaluation)
- Contribute towards the team’s research tooling and its efficiency
- Help establish a collaborative mindset and shared ownership
REQUIREMENTS
- Bachelor’s degree or higher in mathematics, statistics, computer science, or similar quantitative discipline
- 3+ years of work experience in systematic alpha research in equities using high frequency/intraday data
- Fluency in data science practices, e.g., feature engineering, signal combining
- Technically comfortable handling large datasets
- Comfortable coding in both C++ and Python in a Linux environment
- Exposure working with cloud computing platforms such as AWS
- Highly motivated and willing to take ownership of his/her work
- Collaborative mindset with strong independent research ability
- Commitment to the highest ethical standards
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: AWS Computer Science Engineering Feature engineering Linux Mathematics Python Research Statistics Trading Strategies
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