Systematic Fast Trading Intern

About the role

Summer internship in Man Group’s New York Fast Trading Strategies team, supporting high-frequency alpha research, trading, and infrastructure. The team seeks PhD students for MLE or quantitative researcher work involving machine learning, tick data, research workflows, model deployment, and strategy development. Internship expected to last 10–12 weeks.

The Team

• Develops high-frequency trading strategies across global futures and cash markets.
• Uses machine learning, event-driven methods, and market microstructure techniques to capture fast alpha.
• Builds customized monetization systems and optimizes trading and order placement using high-frequency infrastructure.

Role Responsibilities

• MLEs develop software for machine learning applications, including MLOps and research workflows.
• Quantitative researchers use high-frequency tick data and machine learning to predict asset returns.
• Convert predictive models into profitable trading strategies and work with MLOps on model deployment.
• Contribute to end-to-end development of the fast alpha portfolio.

Eligibility

• Open to PhD students in highly technical degree programs with strong academic achievement.
• Summer internships are open to penultimate-year students only.
• Candidates should have programming experience in multiple languages, especially Python.
• Knowledge of machine learning algorithms and research processes is relevant to the MLE role.

Application

• Submit one application using a university email address.
• Resume must include completed and in-progress post-secondary education GPAs.
• School transcripts may be provided immediately or later during the process.