High - Frequency Quantitative Research Summer 2026 Internship

Man Group•New York, NY

6h•$55 - $65•Onsite

About The Position

Man Group is a global alternative investment management firm focused on pursuing outperformance for sophisticated clients via our Systematic, Discretionary and Solutions offerings. Powered by talent and advanced technology, our single and multi-manager investment strategies are underpinned by deep research and span public and private markets, across all major asset classes, with a significant focus on alternatives. Man Group takes a partnership approach to working with clients, establishing deep connections and creating tailored solutions to meet their investment goals and those of the millions of retirees and savers they represent. Headquartered in London, we manage $227.6 billion and operate across multiple offices globally. As at 31 December 2025 The Team Man Global Markets is responsible for all of Man Group’s execution, spanning all investment engines, asset classes, and regions. The High-Frequency Quantitative Research team, based in New York, is responsible for the research and development of low latency alphas and trading strategies and spearheading the development of Man Group’s proprietary execution algorithms. The team is responsible for full end to end trading strategy development and uses its own customized ML research and monetization infrastructure. Who Should Apply? The team is currently hiring interns with strong academic achievement in highly technical degree programs who are interested in a 2026 summer internship (expected to be between 10 – 12 weeks). Candidates are encouraged to submit only one application using their university email address via the below link, which requires a resume that includes all completed and in-progress post-secondary education GPAs. School transcripts may be optionally provided immediately or later in the process. Kindly note that the summer internship is open to penultimate year students only who will be graduating between Winter – Summer 2027.

Requirements

PhD student or exceptional Masters student in penultimate year of study majoring in a highly quantitative field such as Computer Science, Statistics, Mathematics, Physics, Engineering, or Finance.
Experience in linear and non-linear machine learning algorithms.
Hands-on experience of working with large data sets.
An interest in financial markets modelling and investing.
A deep understanding of statistics and an ability to apply it to real-world problems.
Intermediate skills in at least one programming language (e.g. Python, Java, C, C++).
The ability to communicate complicated ideas in a clear and concise manner.