Quantitative Analyst / Software Developer

com with “202 7 KEPL Application” in the subject line. About Cubist: Cubist Systematic Strategies, an affiliate of Point72, 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.

About Our Team: KEPL is a fast-growing team at Cubist Systematic Strategies. We specialize in trading medium-frequency statistical arbitrage strategies with high Sharpe. The team is made up of people from top universities and top tier trading and tech firms.

We have an open and collaborative culture, and we value rigorous research and innovative technologies. We are actively expanding into new markets and assets classes. Role: We are looking for full-time quantitative research analysts and software developers to join our fast-growing team and contribute to multiple new initiatives that aim to expand our business.

The candidate should have a passion for innovation to solve research and trading problems. In this team, the candidate will gain full-stack exposure and build expertise in multiple aspects of quantitative research and trading. The candidate will play an essential role for the team’s successful expansion.

The candidate will also collaborate with other team members to innovate our research infrastructure which will take our research and trading capability to the next level.

Responsibilities

: Conduct quantitative research to support the team’s investment process. Build technologies that bolster research & trading productivity. Develop, maintain, and improve the production trading capacity.

Expand the system to new markets and asset classes.

Requirements

: Master or PhD degree in math, physics, computer science, engineering, or other related discipline. 1-3 years of professional experience in software development or quantitative research. Strong combination of quantitative skills and programming skills.

Proficiency in Python 3 and either C++ or Java. Familiarity with the Linux environment.