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Hudson River Trading

Quantitative Researcher (Mid-Freq)

New York, United States

Location
New York, United States
Work
Not stated
Employment
Full-time
Level
Not stated
Function
Data & AI
Pay
$175K – $300K a year (read from the ad)
Posted
57 months ago

About the role

HRT is seeking quantitative researchers to join our effort in developing mid-frequency systematic trading strategies. Candidates will apply rigorous statistical methods on a wide range of datasets and implement trading models based on novel predictions of market behavior, all while leveraging HRT’s world-class research and trading infrastructure.

Successful candidates will be part of a growing effort and have the opportunity to contribute to all aspects of strategy development, including alpha generation, portfolio construction/optimization and trade execution algorithms. Researchers are responsible for not only prototyping and conducting research into various strategy components, but also writing code to productionalize their ideas; thus, interest and experience in programming are essential.

HRT employees enjoy a collegial and non-siloed environment; candidates will work closely with other researchers to develop new ideas and refine existing trading models.

Skills

  • 3+ years of prior work experience in stat-arb required
  • Degree in a quantitative or technical discipline (e.g. statistics, computer science, physics, mathematics, economics)
  • Exceptional academic credentials
  • Demonstrated ability to conduct research using large noisy real-world datasets
  • Exceptional attention to detail and desire to understand issues deeply
  • Outstanding work ethic and ability to thrive in a fast-paced environment
  • Strong numerical programming skills, including proficiency in Python for data analysis and machine learning. Experience with C++ a plus

The estimated base salary range for this position is $175,000 to $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.

Please be advised: Use of AI tools by an applicant during interviews or assessments is strictly prohibited, unless otherwise instructed or agreed upon. We employ various methods to evaluate the authenticity of candidate responses. If we determine that AI assistance was used by an applicant during an interview or an assessment, we reserve the right to immediately end the interview or assessment, disqualify the applicant’s candidacy and/or rescind any job offers extended.

You can review our Global Applicant Privacy Notice, which explains how we process applicant information.

Source

Posted by Hudson River Trading on their own hiring page, www.hudsonrivertrading.com. OptiTalent shows it as published, read 07 Nov 2026 02:09 UTC; the original is the reference.

View the original ad ↗

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