Algorithm Developer (Quant Research & Trading) – 2027 PhDs

About the role

Join Hudson River Trading’s Algorithm Development team as a full-time PhD candidate building and maintaining predictive trading models. Apply statistical analysis, machine learning, and advanced research to market data, develop order-execution methods, run models on high-performance infrastructure, and analyze performance across global markets.

Role and Responsibilities

• Build and maintain models that drive trading activities.
• Apply statistical analysis to extensive market and financial datasets.
• Research, develop, and test novel order-execution and model-training methods.
• Run models live on high-performance trading infrastructure.
• Analyze daily performance to maintain ongoing profitability.
• Collaborate with Algorithm Developers and Software Engineers on technical problems.

Locations and Working Style

• Positions are available in New York, London, and Singapore.
• Apply academic research expertise to real-world trading problems across time horizons and machine-learning strategies.
• Identify opportunities in worldwide markets through self-guided research and collaboration.
• Work creatively and independently on long-term technical problems in a fast-changing environment.

Requirements

• Currently pursuing a full-time PhD in mathematics, physics, computer science, statistics, or a related quantitative discipline.
• Eligible for full-time roles in 2027.
• Fluent in Python.
• Experience with statistical analysis, numerical programming, or machine learning.
• Experience with Pandas, NumPy, R, and/or MATLAB.
• Demonstrated analytical and problem-solving ability.

Application and Compensation

• Submit one application only; HRT will consider applicants for all open positions during review.
• US base salary is $300,000; other locations offer locally competitive base salaries.
• Total compensation includes a sign-on bonus and discretionary performance bonus.
• Company-paid medical and/or other benefits are provided.
• AI tools are prohibited during interviews or assessments unless expressly permitted.