Jobs at Citadel

Develop high-performance C++ systems for systematic investing, including real-time data processing, low-latency trading execution, and machine-learning inference tools. Design scalable distributed systems and resilient data pipelines, maintain critical production platforms, and build greenfield solutions in collaboration with quantitative researchers. Ensure software correctness, reliability, performance, and fail-safe operation in live-market environments while aligning technical work with business value.

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

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

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

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.

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) 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.

Conduct quantitative investment research by building predictive models, applying statistical and mathematical techniques, optimizing multi-asset portfolios, and developing optimization algorithms. Analyze financial markets, price formation, and risk using large-scale data and coding in C++ or Python. Collaborate with researchers, engineers, and traders to develop scalable systems and identify investment opportunities.

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

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.

Conduct innovative machine learning research and develop scalable, robust models for financial markets across asset classes. Apply deep learning, sequence and time-series modeling, natural language processing, large language models, pre-training, fine-tuning, and reinforcement learning to model price formation, market behavior, and risk. Design, implement, optimize, and deploy models using Python and modern machine learning frameworks while collaborating with quantitative researchers, engineers, and traders.

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.

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