Global Quantitative Research Summer Associate Program - 2027

About the role

The 2027 Cross-Asset Quantitative Research Summer Associate Program offers graduate students up to three rotations across credit, rates, equities, derivatives, and systematic investment strategies. Associates conduct quantitative research using machine learning, data science, financial modelling, and derivatives analysis to develop investment, trading, asset allocation, and hedging strategies.

Program Structure

• Complete up to three rotations across cross-asset quantitative research teams.
• Potential groups include credit strategy, rates and rate derivatives strategy, and US equity strategy.
• Additional rotations may include equity derivatives research and quantitative systematic investment strategies.

Responsibilities

• Apply machine learning to develop risk-premia harvesting and asset allocation strategies.
• Use data science to model rates curves, positioning, portfolio construction, and market anomalies.
• Identify credit-market distress indicators and earnings inflection points using real-time and big data.
• Model derivatives to identify mispriced assets and develop alpha-generating trading strategies.
• Develop dynamic hedging solutions to improve risk management of client assets.

Requirements

• Pursue a Master's or Ph.D. in quantitative finance, financial engineering, or a related technical field.
• Graduate between November 2027 and June 2028 from an accredited college or university.
• Have experience managing and analysing large datasets with modern data-science tools.
• Know Python and Excel; machine-learning packages are required for certain rotations.
• Understand advanced machine learning techniques, particularly for selected rotations.
• Understand futures, options, and underlying pricing models for derivatives-team rotations.

Additional Qualifications

• Communicate complex ideas clearly and concisely to non-technical individuals.
• Demonstrate distinguished written and verbal communication skills.
• Work independently and drive projects toward completed end products.
• Maintain strong attention to detail and quality control over personal work.
• Show research passion, curiosity, and the ability to deliver results under uncertainty.