Junior Treasury Quant Researcher

Hudson River Trading (HRT) is seeking a Quantitative Researcher focused on Treasury Optimization and Research to join our PostTrade team. In this role, you’ll work closely with our Funding, Finance, and Treasury Engineering teams to develop HRT's Treasury optimization and enhance funding & capital efficiency. Researchers at HRT work on small, highly productive teams that design, analyze, and maintain the models and strategies that drive the efficiency and profitability of our business. As a member of our PostTrade team, you will be challenged by dynamic financial markets and contribute to critical optimization models in an extremely fast-paced setting. The ideal candidate is a brilliant quantitative mind who enjoys solving complex problems, values a highly collaborative culture, and thrives in a performance-driven environment. 

Responsibilities 

• Build and enhance the quantitative components of HRT’s Treasury Optimization Platform, including designing and developing optimization models to improve funding efficiency and collateral allocation across global markets
• Conduct research to expand funding & collateral modeling and analytical capabilities, and identify new opportunities to maximize returns
• Collaborate with partners across Funding, Finance, and Engineering teams to integrate research and analytics into production systems, streamline cash and collateral workflows, and develop comprehensive metrics for funding, margin, and counterparty management

Qualifications

• Bachelor’s, Master’s, or PhD in Computer Science, Engineering, Mathematics, Statistics, Physics, Operations Research, or a related quantitative field
• Exceptional problem-solving skills, with a strong foundation in mathematical, statistical, or optimization fundamentals
• Strong programming skills, with solid experience in Python
• Proficiency with numerical computing or machine learning libraries (e.g., NumPy, Pandas, PyTorch, TensorFlow) is a significant advantage
• Familiarity with optimization techniques, such as gradient descent and linear/convex programming, is highly desirable
• Knowledge of portfolio financing, funding mechanics, prime brokerage, or risk management frameworks is a plus
• Excellent cross-functional communication skills, with the ability to work effectively with engineers, researchers, and financial professionals

The estimated base salary range for this position is $150,000 - $200,000, based on job-related skills and experience. This role will also be eligible for discretionary performance-based bonuses and a competitive benefits package.