Top Internships

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

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.

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.

Build high-performance tools and large-data research platforms to enable trading strategies. Work in small engineering teams to design systems, develop platforms and web frameworks, and apply techniques such as distributed computing, NLP, and machine learning to solve complex problems.

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

Conduct quantitative research for investment strategies using advanced statistical and mathematical modeling, machine learning, data analysis, portfolio optimization, and algorithm development. Build predictive models and analyze price formation, risk, and financial market drivers. Collaborate with researchers, engineers, and traders to develop scalable systems and solve real-world investment problems.

Collaborate with quantitative researchers to analyze data, develop research tools, and enhance and maintain automated trading systems and algorithms. Build scalable software solutions using quantitative techniques to address complex financial problems. The role requires strong programming, Linux development experience, creative problem-solving, business-value prioritization, and effective stakeholder communication.

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