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GTS

Quantitative trading with AI market making

Quantitative Trader - ETF Team, Fixed Income

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

About the Job

Requirements

  • At least 1 year of experience working as a quantitative trader with fixed income or fixed income exchange-traded fund products.
  • A Bachelor of Science or Master of Science degree from a leading university in a quantitative discipline such as mathematics, physics, statistics, computer science, engineering, or economics.
  • Deep understanding and ability in mathematics and statistics.
  • Strong programming skills in kdb/q and/or Python.

Responsibilities

  • Work on existing trading strategies with the goal of becoming capable of designing, building, and managing profitable trading strategies as part of a multidisciplinary team.
  • Work on projects across the quantitative trading space within the fixed income exchange-traded fund space.
  • Work closely with senior traders on strategies.
  • Gain insight into how the trading desk operates and how traders evaluate trading opportunities.
  • Apply work directly to the group's activities and help drive revenue.

Desired Qualifications

  • Experience in fixed income markets or fixed income exchange-traded funds.
  • A strong quantitative background.
  • A GPA over 3.6 on a 4.0 scale.

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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