Top Tech Jobs & Startup Jobs

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.

Partner with quantitative researchers to design, build, optimize, and scale deep learning models and tooling for research and production. Work includes model architecture, distributed training, inference optimization, ML libraries, and high-performance computing to improve training speed, scalability, reliability, and cost-efficiency in systematic investing workflows.

Intern will help turn quantitative research into production equities trading strategies, optimize portfolio allocation and risk, minimize trading costs and market impact, monitor performance, and perform statistical research to improve risk-adjusted returns while making real-time allocation decisions under supervision.

The Citadel Associate Program offers undergraduates hands-on training in equities investing, focusing on financial modeling, company analysis, and investment research, with direct collaboration with investment teams.

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

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

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

Develop and improve mathematical models and trading approaches. Conduct statistical analysis and back test trading strategies in a fast-paced environment.

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.

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.