Quantitative Software Developer

Quantitative Software Developer New York 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. KEPL is a fast-growing team at Cubist Systematic Strategies. We are specialized in 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, including: D.E. Shaw, Two Sigma, Citadel, Meta, Google, etc. We have an open and collaborative culture, and we value rigorous research and innovative technologies. Please send CVs to with "2025 KEPL QD Application" in the subject line. We are looking for a quantitative software developer to join our team and contribute to multiple initiatives that aim to expand our business. The candidate should be passionate about financial market, data and technology. In this team, the candidate will gain full-stack exposure and build expertise in multiple aspects of quantitative trading. Responsibilities: Improve data ETL pipeline and build tools to analyze new data efficiently. Build technologies to bolster research & trading efficiency. Expand to new markets and asset classes. Manage day-to-day operations in a fast-paced environment. Requirements: Master/PhD degree in math, computer science, engineering, or other related fields. 1-3 years of professional experience in software development or data science/analytics. Strong combination of quantitative skills and programming skills. Proficiency in Python; knowledge of common data analytics tools (e.g., SQL, pandas) is a plus. Familiarity with the Linux environment. Excellent written and verbal communication skills. Willing to work in a fast-paced start-up environment. Commitment to the highest ethical standards.