Jobs at Citadel

11-week quantitative research internship developing and implementing mathematical and trading models. Responsibilities include model conceptualization, backtesting, live implementation, using unconventional data, and conducting statistical research to refine trading signals and monetization systems.

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

Human Resources Interns support global HR projects and processes, identify process-improvement opportunities, analyze HR data, and develop solutions to talent challenges. They collaborate with stakeholders across People Operations, Benefits, Learning and Development, and People Analytics. The role requires strong communication, organization, analytical and problem-solving skills, along with proficiency in Excel, PowerPoint, and familiarity with AI tools such as Gemini and Claude.

11-week software engineering internship building high-performance, large-data research platforms and trading tools. Work in small teams on system architectures, distributed systems, NLP and ML, and web frameworks while collaborating with senior engineers.

Build scalable software, data pipelines, analytical infrastructure, and research tools for investment teams. Translate quantitative models and research ideas into reliable production systems, collaborate with researchers, portfolio managers, traders, and engineers, and solve technically challenging data-intensive problems. The role requires strong Python and software engineering fundamentals, experience with complex datasets, communication skills, adaptability, and interest in financial markets.

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.

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.

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

Leads strategy, roadmap, design, launch, and scaling of data-driven health and human performance programs. Evaluates care models and digital health technologies, develops business cases and product requirements, manages vendors and cross-functional stakeholders, tracks outcomes, and drives program iteration. Partners with the Chief Medical Officer and Benefits team on health services, analytics, healthcare navigation, and employee health initiatives.

Design, develop, test, deploy, and maintain scalable Java applications, services, and platforms supporting investment and business workflows. Build distributed systems, APIs, data platforms, and event-driven architectures; modernize existing technology; improve performance, reliability, and scalability; and contribute to architecture and technical strategy. Partner with users and engineering teams throughout the software development lifecycle to deliver production-quality solutions.

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.

Design, develop, test, deploy, and maintain high-performance C++ systems, services, libraries, and platforms. Solve complex challenges involving performance, latency, concurrency, scalability, and distributed systems. Collaborate with engineers and investment professionals, build new systems, optimize production platforms, contribute to architecture and developer tooling, and own technology throughout its lifecycle.

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

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.

Participate in an 11-week Operations internship supporting clearing, settlements, corporate actions, collateral management, and shared services. Analyze business needs using data, develop and implement strategic process improvements, manage team projects end-to-end, collaborate across global teams, and contribute to a cross-functional capstone initiative focused on advancing Operations.

Investment Associates analyze companies and industries for investment opportunities, conducting valuations and financial modeling, and participating in investor communications.

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.

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.

Develop and deploy advanced statistical and ML models on large-scale alternative datasets to generate investable signals, partner with investment teams, evaluate data quality, and drive novel data-driven research with commercial impact.

Optimize and manage portfolio-level trading strategies by translating quantitative research into production. Tune allocators and risk, minimize trading costs and market impact, monitor performance in real time, and conduct statistical research to improve risk-adjusted returns.