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Participate in a structured fixed income and macro trading rotation. Develop expertise in financial markets, apply statistical techniques to trading, adapt investment approaches, and use advanced trading technology. Collaborate with traders, quantitative researchers, and technologists while identifying opportunities and managing risk. The internship also includes networking with senior team members and peers.

Develop and evolve investor-facing equity products from discovery through launch and iteration. Build high-performance, data-intensive interfaces using React and TypeScript for research, risk, portfolio, and investment workflows. Collaborate with investors, product managers, UX designers, and engineers to identify opportunities, shape product strategy, prototype solutions, and deliver maintainable, well-tested software with strong commercial impact.

As a Quantitative Developer, you'll innovate and enhance quantitative methods, develop custom tools, maintain data pipelines, and collaborate with researchers for advancing investment strategies.

11-week internship building high-performance research platforms and trading tools. Work in small teams on distributed systems, NLP/ML applications, and web frameworks while collaborating with senior engineers.

Serve as a senior HR advisor to EMEA Fixed Income and Macro leaders. Lead workforce planning, organizational design, succession planning, talent assessment, performance management, compensation and promotion decisions. Use workforce data to provide insights, guide organizational priorities, and measure talent initiatives. Partner with the Head of People and global People teams, coach leaders and junior HR staff, and drive cross-business talent initiatives across multiple EMEA markets.

Build high-performance tools and large-data research platforms to enable trading strategies. Work in small engineering teams to design systems, develop platforms and web frameworks, and apply techniques such as distributed computing, NLP, and machine learning to solve complex problems.

Quantitative Research Engineers at Citadel's GQS develop software solutions, enhance trading systems, and collaborate with researchers to apply quantitative techniques.

Develop modern C++ systems for systematic investing, including low-latency data processing, high-frequency trading execution, quantitative analytics libraries, and machine-learning inference tools. Collaborate with quantitative researchers to build scalable, reliable, and performant production platforms, design distributed data pipelines, evaluate system architectures, and maintain fail-safe live-market trading infrastructure.

Commodities Analysts generate commodity investment ideas through fundamental research and data analysis, focusing on modeling supply and demand and improving data quality.

Partner with quantitative researchers to design, build, optimize, and scale deep learning models and tooling for research and production. Work includes model architecture, distributed training, inference optimization, ML libraries, and high-performance computing to improve training speed, scalability, reliability, and cost-efficiency in systematic investing workflows.