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Hudson River Trading

Trades financial markets with automated models

Algorithm Developer - Quant Research & Trading, 2027 Phds

Quantitative Trading / Algorithm DevelopmentConfirmed live in the last 24 hours
Full-timeIn-person

About the Job

Requirements

  • You are a full-time PhD student in a quantitative discipline such as mathematics, physics, computer science, statistics, or a related program, and are eligible for full-time roles in 2027.
  • Fluency in Python.
  • Experience with statistical analysis, numerical programming, or machine learning in Python.
  • Experience with Pandas, NumPy, R, and/or MATLAB.
  • Ability to work creatively and independently on long-term technical problems.

Responsibilities

  • Build and maintain the models that drive trading.
  • Research, develop, and test novel order execution and model training methods to increase trading efficiency.
  • Run models live on high-performance trading infrastructure.
  • Analyze daily performance to maintain ongoing profitability.
  • Apply advanced academic research expertise to real-world trading problems across time horizons and machine learning strategies.
  • Identify new opportunities in worldwide markets and analyze and fix problems efficiently.

Desired Qualifications

  • Brilliant analytical and problem-solving skills.

About the Company

Hudson River Trading

Trades financial markets with automated models

Hudson River Trading buys and sells financial products through automated models, supplying liquidity that lets other market participants trade on exchanges and directly with the firm. Its business spans equities, futures, options, currencies, and fixed income, with research rooted in mathematics and computer science. Researchers develop and test trading strategies against market data, while engineers build the computing systems that run those strategies and manage their risks. The firm earns income from its trading activity across these markets, with teams combining quantitative research and trade execution. Hudson River Trading was founded in 2002 and is headquartered in New York City.

Company size
1,001-5,000
Company stage
Debt Financing
Total funding
$630M
Headquarters
New York City, New York
Founded
2002

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