Hudson River Trading (HRT) is seeking exceptional full-time PhD students to join our Algorithm Development team. Algorithm Developers are responsible for building and maintaining the models that drive our trading. A typical day involves applying rigorous statistical analysis to vast quantities of market and financial data to produce predictive trading models.
In this role, you will work alongside fellow Algorithm Developers and Software Engineers to research, develop, and test novel order execution and model training methods to increase trading efficiency. This will involve running models live on our high-performance trading infrastructure and analyzing daily performance to maintain ongoing profitability. You can expect to apply your advanced academic research experience and expertise to impactful real world problems in trading across time horizons and machine learning strategies.
Profile
- You’re excited to apply your research expertise to identify new opportunities in worldwide markets
- You enjoy both self-guided research and collaborating with others to analyze and fix problems efficiently
- You are a critical thinker who can learn and implement new skills in a fast-changing environment
Qualifications
- You are a full-time PhD student in a quantitative discipline (math, physics, computer science, statistics, or a related program) who is eligible for full-time roles in 2026
- Fluency in Python
- Experience with statistical analysis, numerical programming, or machine learning in Python, Pandas/Numpy, R, and/or MATLAB
- Brilliant analytical and problem-solving skills
- Ability to work creatively and independently on long-term technical problems
The estimated base salary for this position is $300,000 per year, based on job-related skills and experience. This role will also be eligible for discretionary performance-based bonuses and a competitive benefits package.
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.
Top Skills
What We Do
Hudson River Trading 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.
Why Work With Us
At HRT we are mathematicians, computer scientists, statisticians, physicists and engineers. We believe that by cultivating an environment that encourages idea sharing and collaboration, we develop our best strategies. We boast a flat management structure as all our people are motivated by being at the forefront of the automated trading world.
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Hudson River Trading Offices
Hybrid Workspace
Employees engage in a combination of remote and on-site work.
Teams have a range of in-office needs: some require 24/7 coverage or hands-on maintenance, while others operate across time zones. While the majority of teams adopt a fairly even split between in-office and remote work, many come in every day.
