Skills

Communication Python Matlab Data Analysis Statistical Analysis Research Machine Learning Programming Organization Numpy Pandas C++ Mathematics

Job Specifications

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 have the opportunity to rotate between our high-frequency trading, multi-frequency trading, and/or machine learning teams. In close collaboration with your mentors, you will apply sophisticated quantitative modeling techniques to understand and predict market behavior and write software to improve our trading strategies.

We are looking for quantitatively-driven and practically-minded programmers, scientists, and mathematicians who are excited to solve the most challenging problems in our field.

What To Expect

Leverage our proprietary infrastructure (Python/C++) in conjunction with third-party tools to conduct quantitative research and data analysis
Use machine learning and time series techniques to derive novel insights on market behavior from large and complex datasets
Work on impactful projects in close collaboration with experienced researchers, traders, and developers
Use our world-class compute cluster to run simulations and crunch data
Build predictive models for financial markets using a combination of market and non-market data
Attend and participate in Tech Talks that provide an overview of markets and HRT’s trading philosophy
Enjoy a curriculum of speakers, trading games, mentorships, and social events throughout the summer

Qualifications

You are a full-time undergraduate, masters, or PhD student in a quantitative discipline (math, physics, computer science, statistics, or a related program) who is eligible for full-time roles in 2027
Experience programming in Python is a must; C++ is a plus for those interested in high-frequency trading
Experience with statistical analysis, numerical programming, or machine learning in Python, Pandas/Numpy, R, and/or MATLAB
A passion for applying quantitative models and technology toward solving real-world problems
Strong communication skills

Culture

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. We’re a community of self-starters who are motivated by the excitement of being at the cutting edge of automation in every part of our organization—from trading, to business operations, to recruiting and beyond. We value openness and transparency, and celebrate great ideas from HRT veterans and new hires alike. At HRT we’re friends and colleagues – whether we are sharing a meal, playing the latest board game, or writing elegant code. We embrace a culture of togetherness that extends far beyond the walls of our office.

Feel like you belong at HRT? Our goal is to find the best people and bring them together to do great work in a place where everyone is valued. HRT is proud of our diverse staff; we have offices all over the globe and benefit from our varied and unique perspectives. HRT is an equal opportunity employer; so whoever you are we’d love to get to know you.

About the Company

At Hudson River Trading (HRT) we are mathematicians, computer scientists, statisticians, physicists and engineers. We research and develop automated trading algorithms using advanced mathematical techniques. We have built one of the world's most sophisticated computing environments, and our researchers are at the forefront of innovation in the world of algorithmic trading. HRT’s founding partners graduated from Harvard and MIT with degrees in computer science and mathematics, and founded HRT in 2002. Armed with programming ... Know more