Algorithm Development (Quant Research & Trading) Internship - Summer 2027
Hudson River Trading
Multi-location internship (London/New York/Singapore) with a stated London weekly base salary of GBP 4,350. Rolling deadline. Only one application allowed per candidate across HRT roles.
Full job description
Hudson River Trading (HRT) is seeking exceptional full-time students to join our Algorithm Development Summer Internship Program. Algorithm Developers at HRT focus on the research and implementation of automated trading strategies. As an intern, you will rotate between high- and mid-frequency trading teams, as well as machine learning teams, applying sophisticated quantitative modeling techniques to understand and predict market behavior. What to Expect: leverage proprietary infrastructure (Python/C++) to conduct quantitative research and data analysis; use machine learning and time series techniques to derive novel insights on market behavior; work on impactful projects with experienced researchers, traders, and developers; utilize a world-class compute cluster to run simulations; attend Tech Talks and a curriculum of speakers, trading games, mentorships, and social events throughout the summer. Qualifications: a full-time undergraduate or master's student in a quantitative discipline (math, physics, computer science, statistics, or a related program); experience programming in Python is a must (C++ desired for low-latency trading); experience with statistical analysis, numerical programming, or machine learning in Python, Pandas/Numpy, R, and/or MATLAB. Weekly base salary: New York USD 5,800; Singapore SGD 7,650; London GBP 4,350, plus a signing bonus, company-paid housing, and meals. Hudson River Trading (HRT) brings a scientific approach to trading financial products. We have built one of the world's most sophisticated computing environments for research and development. Our researchers are at the forefront of innovation in the world of algorithmic trading. At HRT we welcome a variety of expertise: mathematics and computer science, physics and engineering, media and tech.