Jobs at Citadel

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.

Work with engineering teams to build, deploy, and maintain production systems. Automate repetitive tasks, own incident management, improve reliability and performance, and design scalable solutions using SRE principles.

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

Quantitative Researchers at GQS leverage advanced statistical techniques and machine learning for investment strategies, portfolio optimization, and innovative research.

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

Summer internship on an international long-short equities team. Learn financial modeling, conduct primary and quantitative research, use third-party data, and gain exposure to research technology and risk systems to support investment decisions.

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.

Quantitative Researchers work on developing mathematical models, backtesting trading strategies, and conducting statistical analysis, utilizing complex data sets and algorithms.

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.

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

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

Develop mathematical models and trading strategies, back test trading models, conduct research and statistical analysis for monetization systems.

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.

Engineers at Citadel work in small teams to develop high-performing technology under quick cycles. They focus on creating tools for trading strategies and data research platforms.

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.

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

The role involves developing and improving mathematical models for trading, analyzing statistical data, backtesting trading models, and using unconventional data for insights.