We are seeking experienced software engineers to join our effort in developing the next generation of trading strategies at Hudson River Trading. As a quantitative research engineer, you will be embedded within a trading team focused on building the technology that powers our medium-frequency systematic trading capabilities.
Responsibilities
- Improve the performance and reliability of our signal research, historical simulation, portfolio construction, and optimization platforms
- Build new tools for conducting statistical analysis over large datasets
- Design infrastructure that effectively leverages our cutting-edge compute cluster
- Work with quantitative researchers to translate their needs into scalable, standardized solutions
- Develop and execute pipelines for onboarding new data sources for ingestion in research and production
- Establish an engineering culture within the trading team, advocating for coding best practices and guiding adoption decisions for open-source tools and packages
Requirements
- Degree in computer science, engineering, or a similar technical discipline
- 3+ years of professional software engineering experience with Python as a primary language
- Significant experience working with Python scientific computing packages (numpy, scipy, pandas, matplotlib, sklearn, etc.)
- Commitment to building well-designed, reliable, and maintainable software
- Passion for building tools that empower researchers
- Outstanding work ethic and ability to thrive in a fast-paced environment
- Strong quantitative reasoning skills and an interest in working at the intersection of research and software engineering
Annual base salary range of $175,000 to $250,000. Pay (base and bonus) may vary depending on job-related skills and experience. A sign-on and discretionary performance bonus may be provided as part of the total compensation package, in addition to company-paid medical and/or other benefits.
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.
