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Conduct research and develop machine learning models for finance, focusing on deep learning and large language models, optimizing them for performance, and collaborating with teams to integrate ML solutions.

Translate mathematical models into ultra-low latency implementations, optimize trading algorithms, and develop high-performance C++ systems for real-time trading.

Design, prototype, and build high-performance, real-time web applications and visualizations for investment professionals. Gather requirements, partner with traders and researchers, deliver scalable UIs, and improve platform workflows and performance.

Quantitative Researchers at Citadel Securities develop automated trading strategies using statistical techniques and implement them in live environments.

Conduct ML/AI research to extract patterns from diverse datasets (including unstructured data), implement algorithms in high-quality code, back-test models, and document findings for quantitative trading applications.

PhD internship conducting research applying statistics, machine learning and AI (e.g., deep learning, NLP) to market data. Implement and test algorithms in production-quality code, work with large and unstructured datasets, back-test models, and document findings while collaborating with senior researchers.

Conduct original research applying machine learning, deep learning, and NLP to extract patterns from large and unstructured datasets; implement and back-test algorithms in high-quality code; document findings and collaborate with trading teams to deploy research-driven models.

The intern will develop trading strategies, back test models, analyze data, and collaborate with the research team to innovate and refine monetization systems.

12-week internship designing, implementing, and testing FPGA solutions for ultra-low latency trading systems. Work in small teams to improve trading system efficiency, perform RTL coding, simulation, synthesis, validation and integration, and collaborate with senior engineers.

11-week internship performing quantitative research to develop, backtest, and implement automated trading strategies. Translate mathematical models into code, analyze unconventional data sources, conduct statistical research (ML, time-series, NLP), and collaborate with senior researchers to refine trading signals and monetize models.