GTS is a quantitative trading firm operating at scale—accounting for ~5% of U.S. cash equities volume and serving as Designated Market Maker for 800+ NYSE-listed companies. The tech stack reveals a low-latency trading infrastructure built on C++, Python, kdb+, and FPGA design tooling (Xilinx, Cadence, Synopsys), with active investment in network automation and CI/CD pipelines for configuration management—indicating ongoing optimization of execution speed and operational resilience. Hiring patterns show finance and engineering nearly equal (11 finance, 5 engineering roles), a sales-focused motion, and geographic expansion beyond New York into UK and Poland.
GTS combines quantitative trading with infrastructure engineering to operate global electronic markets. The firm trades equities, ETFs, fixed income, futures, and FX, with proprietary systems handling ~1 billion shares daily. As a designated market maker for major NYSE-listed companies representing ~$17 trillion in market cap, GTS provides liquidity solutions to institutional clients, public companies, and retail investors. The organization spans ~300 employees across New York headquarters, U.S. offices, and European locations. Core operations blend algorithmic trading strategy development, low-latency network design, and trader-facing analytics tools.
GTS runs C++, Python, Java, and kdb+ on Arista and Cisco network infrastructure, with FPGA design tooling including Xilinx, Cadence, and Synopsys for ultra-low-latency execution. Bloomberg integration provides market data and reference systems.
Active projects include systematic trading strategy development in futures and FX, network automation platform upgrades, CI/CD infrastructure for network configuration, next-generation network design, and analytics tools for traders. Internal focus areas address latency reduction and algorithmic P&L improvement.
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GTS's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.