Jobs at Citadel

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.

Develop and improve mathematical models for trading strategies, conduct research and statistical analysis in a fast-paced team environment.

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.

Early-career data scientist supporting sector investment teams: deliver data pulls, analyses, trackers, dashboards, anomaly investigations, and reusable Python/SQL tooling. Use time-series methods, alternative data, and LLMs to accelerate workflows and build commercial judgment with investors.

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.

Summer 2027 internship supporting Sector Data Scientist and investment teams by acquiring, cleaning, and analyzing multiple data sources, testing investment hypotheses, identifying key data drivers and inflection points, and presenting research and decision-support tools to inform investment decisions.

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.

The role involves physical gas trading, analysis, and scheduling, requiring keen knowledge of U.S. gas markets and collaboration with internal stakeholders.

Develop, test, and deploy software solutions for automated trading systems in partnership with Quantitative Researchers. Implement high-performance, scalable systems using advanced quantitative techniques, distributed computing, ML/NLP, and strong software engineering practices. Collaborate on priorities, deliver custom solutions, and engage with senior team members during an 11-week internship.

The Recruiting Coordinator collaborates with recruiters to manage the hiring process, schedule interviews, and maintain candidate pipelines, requiring strong communication and organizational skills.

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.

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.

As a Quantitative Research Engineer, design, develop, and implement software for automated trading systems using advanced statistical techniques. Collaborate with researchers and prioritize business needs.

As a PhD intern, you will design and develop software solutions for automated trading systems, collaborating closely with the Quantitative Research team.

Support trade lifecycle activities including clearance, settlement, and cash management. Collaborate with trading/financing desks, counterparties, and custodians. Identify and implement process and technology improvements, perform data analysis (Excel), and learn securities financing and prime brokerage workflows.

As a Quantitative Researcher Intern, you'll develop models and strategies, conduct statistical analysis, and implement algorithms in a trading context.

Develop high-performance research platforms and tools that bring trading strategies to life. Work in small teams to design, build, and deploy resilient systems using distributed computing, NLP, and machine learning to solve large-data problems in finance.

Support investment teams by acquiring, cleaning, and analyzing multi-source data to test investment theses, identify inflection points, and present research. Learn fundamental investor approaches, build decision-support tools, and communicate findings clearly to Sector Data Analysts and investment teams.