Quantitative Portfolio Manager

About Cubist

Cubist Systematic Strategies, part of Point72, focuses on deploying automated, data-driven trading strategies across several liquid asset classes such as equities, futures, and foreign exchange. Our approach is grounded in meticulous research leveraging extensive public data to identify market anomalies.

Role Overview

• Manage portfolio risk dynamically by analyzing both past and real-time performance of trading strategies.
• Supervise and control automated trade execution while keeping transaction costs under close watch.
• Lead a compact team of researchers and developers daily, coordinating efforts and guiding projects.
• Design and implement sophisticated investment strategies by developing advanced quantitative financial modeling tools for research and analysis.
• Source and analyze historical and live data necessary for constructing and refining investment models.
• Create and integrate complex quantitative algorithms connecting diverse datasets from multiple providers.
• Develop investment models that produce buy and sell signals by applying quantitative, mathematical, statistical methods, forecasting risk, returns, and trading expenses.
• Utilize quantitative methodologies to appraise securities valuations.
• Perform innovative and ongoing quantitative research aimed at enhancing existing strategies and exploring new market opportunities.
• Contribute to the development of effective statistical models, emphasizing forecasting techniques and optimization methods.
• Expand the scope and volume of trading activities, including entry into new exchanges and asset classes.

Professional Requirements

• Possession of an advanced degree such as a Master's or Ph.D. in computational or analytical disciplines.
• At least 10 years of relevant experience in researching, developing, or applying quantitative models encompassing equities, futures, and/or foreign exchange.
• Practical expertise covering comprehensive research workflows: methodology design, data acquisition and processing, testing, prototyping, backtesting, and ongoing evaluation of model performance.
• Demonstrated intellectual curiosity and innovative mindset with a strong interest in financial markets and behavioral patterns.