Quantitative Latency Engineer

Hudson River Trading (HRT) is seeking curious, thoughtful engineers who enjoy working with data and solving real-world technical problems to join our growing Market Structure Analysis team. In this role as a Quantitative Latency Engineer, you’ll apply data-driven methodologies to understand and optimize trading technology and real-time interactions with financial markets across the globe, spanning traditional and crypto exchanges. No prior finance experience is needed!

Analyze time series network and exchange protocol captures

• Become familiar with the details of specific markets, attend presentations and liaise with exchange counterparts
• Research exchange features, capabilities, and architecture
• Automate collection and visualization of metrics that quantify efficacy of exchange communication
• Formulate and conduct controlled experiments that measure impact of calculated changes to HRT’s trading infrastructure
• Communicate ideas, requirements, and results across disparate teams
• Improve fill rate of our hardware-based trading strategy
• Reduce incidence of cancel-reject responses
• Investigate and report details of various latency-sensitive exchanges Profile
• You possess a degree in Data Analytics or a related field
• You can collect and interpret network and/or financial market data
• You have professional experience in latency reduction, preferably in finance
• You have a basic understanding of proprietary trading and exchange technologies

Proficiency in data analytics including statistics, data visualization, and working with large data sets - Basic understanding of TCP and UDP network protocols - Extensive experience with Python and relevant data libraries (Pandas, Numpy/Scipy) - Some familiarity with the details of modern computer systems and networks - Experience with real time exchange market data and order entry a plus The estimated base salary range for this position is 200,000 to 300,000 USD per year (or local equivalent).

The base pay offered may vary depending on multiple individualized factors, including location, job-related knowledge, 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.

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