High-Performance Quant Developer - Trading Algorithms

Hudson River Trading; Whitehall; On-site; GBP 194,000 - 268,000; Full time

Benefits offered by this job

Medical benefits

Sign‑on bonus

Discretionary bonus

Job summary

Hudson River Trading is seeking exceptional quantitative thinkers for Algorithm Development roles in New York, London, and Singapore. You will build and maintain predictive trading models, applying statistical analysis to vast market data to improve trading efficiency.

Ideal candidates are strong researchers who can work independently and collaboratively, with experience in Python and/or C++, and a passion for applying quantitative methods to real-world problems.

Qualifications

• Pursuing an undergraduate or master's degree in a quantitative field (math, physics, CS, statistics) eligible for full‑time roles in 2027.
• Experience programming in Python and/or C++.
• Experience with statistical analysis, numerical programming, or ML in Python, Pandas/Numpy, R, or MATLAB.
• Strong analytical and problem‑solving skills; able to work independently and with others.

Responsibilities

• Build and maintain models that drive trading decisions.
• Apply rigorous statistical analysis to large market datasets to create predictive models.
• Collaborate with software engineers to research, develop, and test order execution and model training methods.
• Run models on high‑performance trading infrastructure and monitor daily performance.

Skills

Python programming

C++ programming

Statistical analysis

Machine learning

Education

Undergraduate or master's student in quantitative discipline

Tools

Python

C++

Pandas/Numpy

R

MATLAB

Job description

Hudson River Trading is seeking exceptional quantitative thinkers for Algorithm Development roles in New York, London, and Singapore. You will build and maintain predictive trading models, applying statistical analysis to vast market data to improve trading efficiency.

Ideal candidates are strong researchers who can work independently and collaboratively, with experience in Python and/or C++, and a passion for applying quantitative methods to real-world problems.