Jobs at Citadel

Summer intern role building high-performance, large-data research platforms and web frameworks. Collaborate in small teams to create tools for trading strategies, applying distributed computing, NLP, and machine learning.

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.

SREs at Citadel focus on optimizing and maintaining system reliability, performance, and automation for investment applications, collaborating closely with teams.

Lead trading strategy development and execution for a commodities portfolio, manage risk, conduct analysis, and identify opportunities.

Conduct ML research (deep learning, NLP, statistics) on large and unstructured datasets, implement algorithms in production-quality code, back-test models, and document findings to inform trading strategies.

As a PhD Intern, you will develop mathematical models, conduct statistical analysis, and implement trading strategies while collaborating with senior researchers.

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

As a Quantitative Research Analyst Intern, you will develop and improve trading models, conduct statistical analysis, and collaborate with team members in a data-driven environment.

Develop and deploy advanced machine learning models across asset classes, focusing on deep learning, sequence/time-series modeling, NLP/LLMs, pre-training, fine-tuning, and reinforcement learning. Design and optimize models for performance, scalability, and robustness to model price formation, market behavior, and risk while collaborating with researchers, engineers, and traders.

Conduct ML research (deep learning, NLP) on large and unstructured financial datasets, implement algorithms in high-quality code, back-test models, document findings, and collaborate with senior researchers during an 11-week summer internship in Hong Kong or Singapore.

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

Support investment teams by acquiring, cleaning, and analyzing diverse datasets to test investment theses. Learn fundamental investor approaches, identify key data drivers and inflection points, and present research findings. Work with existing and new data to generate insights and decision-support tools for sector-focused investment research.

The Quantitative Researcher develops trading models and conducts research using complex statistical techniques, requiring a PhD in a quantitative field.

Internship supporting trade lifecycle operations across asset classes. Collaborate with trading/financing desks, counterparties, exchanges, prime brokers and custodians. Perform data analysis and coding, identify process and technology improvements, and help reduce inefficiencies across trade workflows while learning securities financing and market products.

Global Quantitative Researchers at Citadel leverage advanced statistical and quantitative techniques to drive investment strategies and optimize portfolios.

As a Software Engineer at Citadel, you will build systems for investments, collaborate with researchers, and tackle complex problems.