Treasury Optimization Quant Researcher

Hudson River Trading; New York (NY); On-site; USD 150,000 - 200,000; Full time

Job summary

Hudson River Trading (HRT) is seeking a Quantitative Researcher focused on Treasury Optimization and Research to join our PostTrade team. You will work with Funding, Finance, and Treasury Engineering to develop optimization models and enhance funding efficiency across global markets.

The ideal candidate has strong quantitative thinking, expertise in optimization or ML, and proficiency in Python with libraries such as NumPy, Pandas, PyTorch or TensorFlow.

Qualifications

• Strong foundation in mathematical, statistical, or optimization methods.
• Experience with quantitative research in finance is a plus.
• Proficiency in Python and ML libraries.

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.
• 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

Skills

Quantitative analysis

Optimization

Machine learning

Education

Bachelor's/Master's/PhD in a quantitative field

Tools

Python

NumPy

Pandas

PyTorch

TensorFlow

Job description

Hudson River Trading (HRT) is seeking a Quantitative Researcher focused on Treasury Optimization and Research to join our PostTrade team. You will work with Funding, Finance, and Treasury Engineering to develop optimization models and enhance funding efficiency across global markets.

The ideal candidate has strong quantitative thinking, expertise in optimization or ML, and proficiency in Python with libraries such as NumPy, Pandas, PyTorch or TensorFlow.