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Hudson River Trading

Trades financial markets with automated models

Data Scientist Intern

Data ScienceConfirmed live in the last 24 hours
Internship · Summer 2027In-person

About the Job

Requirements

  • Be a full-time student pursuing a degree in a STEM field; a computer science background is not required.
  • Have programming experience with Python at the level of “Python for Data Analysis” by Wes McKinney.
  • Have curiosity about working with data and finding insights.
  • Have exceptional attention to detail.
  • Have strong communication skills.

Responsibilities

  • Normalize and validate vendor data.
  • Extract features from quantitative and textual data.
  • Apply rigorous quality checks.
  • Investigate methodologies for providing the highest quality data for research and trading.
  • Conduct independent data investigation projects using Python and open-source libraries such as pandas and polars.
  • Participate in technical project work and learn about the firm’s research and trading infrastructure and global financial markets.

Desired Qualifications

  • Independent data projects or Kaggle competitions are a plus.

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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