2027 PhD Quantitative Research Intern

About the role

This 10-week internship offers current PhD candidates the opportunity to conduct quantitative research in the Miami metro area, developing predictive signals and improving algorithms for portfolio construction, trade execution, prediction, and risk management. Interns collaborate with researchers, developers, portfolio manager teams, senior colleagues, and peers while contributing to a quantitative trading business.

Responsibilities

• Understand fundamental-domain economics and insights available from related alternative data offerings.
• Identify differentiating factors and design novel predictive signals for quantitative trading applications.
• Backtest and validate research hypotheses using real-world datasets.
• Contribute to algorithms supporting prediction, trade execution, portfolio construction, and risk management.
• Collaborate with researchers, developers, portfolio manager teams, and senior team members.

Internship Experience

• Participate in a 10-week summer internship with opportunities to contribute meaningfully to quantitative trading activities.
• Receive guidance from a dedicated manager and mentor throughout the internship.
• Attend learning sessions, hands-on skills workshops, senior-leader sessions, networking events, and social activities.
• Collaborate and network with peers throughout the internship.

Requirements

• Currently pursuing a PhD in statistics, mathematics, physics, electrical engineering, computer science, or another quantitative technical field.
• Ideally have approximately one year remaining in the academic program.
• Demonstrate excellent programming skills in Python, C, C++, Java, SQL, or R.
• Possess strong knowledge of probability and statistics, including machine learning, time-series analysis, forecasting, pattern recognition, or NLP.
• Communicate research ideas clearly and succinctly.
• Demonstrate creative problem-solving, real-world dataset experience, and strong attention to detail.

Preferred Qualifications

• Previous financial industry experience is preferred but not required.
• An advanced degree in a quantitative or technical field is preferred.