EXPERIENCE

Early Career

REQUIREMENTS:

• MS or PhD in a quantitative discipline
• 0-2 years of professional work experience
• A background in financial markets is not necessary, but an interest in the field is essential
• Proven expertise in Python and handling large datasets
• Fluency in data science practices, e.g., feature engineering. Experience with machine learning is a plus
• Highly motivated, curious, and critical thinker
• Collaborative mindset with strong independent research abilities
• Commitment to the highest ethical standards

ROLE:

A new Cubist portfolio management team specializing in the systematic trading of equities is looking for a Quant Researcher whose core focus will be working on mid-frequency alpha strategies. Joining the team will provide a unique opportunity to be involved with the early stages of a product launch and develop within a growing team.

RESPONSIBILITIES:

• Perform rigorous and innovative research to discover systematic anomalies in the equities market
• End-to-end development, including alpha idea generation, data processing, strategy backtesting, optimization, and production implementation
• Identify and evaluate new datasets for stock return prediction
• Maintain and improve portfolio trading in a production environment
• Contribute to the analysis framework for scalable research