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GTS

Quantitative trading with AI market making

Quantitative Trader/Researcher - Futures

Quantitative Trading / Algorithm DevelopmentConfirmed live in the last 24 hours
Full-timeNew York, NY, USA

About the Job

Requirements

  • A B.S., M.S., or PhD in engineering, mathematics, physics, statistics, or computer science.
  • A minimum of 2 years of experience working on a proprietary trading, quantitative trading, or electronic trading desk at an investment bank, hedge fund, or similar firm.
  • Significant experience with alpha generation and portfolio management.
  • Strong programming skills in C++ and Python are preferred.
  • Working knowledge of Linux and code repository management is preferred.
  • Clear and confident communication skills.

Responsibilities

  • Design, develop, and manage profitable systematic trading strategies in U.S. cash Treasury and futures fixed income, foreign exchange, equity, and commodities markets.
  • Perform independent trading strategy design and research.
  • Collaborate with the technology and trading experts to implement strategies in production.
  • Deploy trading strategies using the existing technology and research platform.
  • Meet the strategy requirements of trading CME futures across all asset classes and cash U.S. Treasuries, supporting high-frequency to mid-frequency trading with overnight activity, fully automated execution, a minimum Sharpe ratio of 3, and at least a one-year production track record.

Desired Qualifications

  • Strong programming skills in C++ and Python.
  • Working knowledge of Linux and code repository management.

About the Company

GTS

Quantitative trading with AI market making

GTS is a group of financial services firms that use market expertise and proprietary technology to provide liquidity across many asset classes. Its core activity is electronic market making through GTS Securities, which quotes and trades to supply liquidity in U.S. cash equities and other markets. The way it works is by applying AI systems and advanced pricing models to automate and optimize trading decisions, enabling faster, more consistent pricing and execution, with a focus on transparency in markets. The company differentiates itself through its quantitative trading heritage, the integration of machine learning and sophisticated pricing tools, and its large presence as a designated market maker at the NYSE, handling a substantial share of trading volume. The goal is to improve market efficiency, reduce trading frictions, and expand the reach of its liquidity and investment capabilities across asset classes.

Company size
201-500
Company stage
Not listed
Total funding
Not listed
Headquarters
New York City, New York
Founded
2006

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