Job Description

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