Quantitative Research (Master's & PhD Summer 2026 Internship) - CHI, NY, BOS, UK

Quantitative Research Intern – Chicago, New York

At BAM, our Researchers collaborate across all asset classes, delivering a wide range of quantitative practices from risk management, big data analysis, AI, LLM, and more. The models built by our QR team power our quantitative strategies and enhance our investment process.

As a QR Intern, you will participate in a hands-on 10-week program designed to advance your research abilities. You will solve complex, real-world problems and make an impact by enhancing our investment and trading frameworks and strategies. The program offers mentorship and collaboration with senior team members, as well as opportunities to expand your network with the broader intern cohort. QR interns are hired into our Systematic, Multi-Asset Arbitrage, Risk and Portfolio Construction teams.

Program Overview and Internship Opportunities

Systematic Research

• Analyze textual data using advanced NLP models to develop actionable trading signals.

Multi-Asset Arbitrage Research

• Build, support, and integrate globally accessible quant trading infrastructure and interact with Portfolio Managers and Quant Researchers to develop requisite toolkits.

Alpha Capture Research

• Develop alphas utilizing LLMs and machine learning methods to enhance trading strategies within an L/S Equity investment team.

Quant Risk Management

• Collaborate with Senior Researchers and Risk Managers to improve framework models and conduct research analyses of the investment process to deliver insights on portfolio construction and risk exposures.

Portfolio Construction Research

• Conduct factor model research and build tools essential to equity factors used throughout the firm.

Qualifications

• Masters or PhD student graduating between December 2026 or May 2027 pursuing a degree in Mathematics, Statistics, Computer Science, or a related quantitative field. Exceptional bachelor’s students with interdisciplinary backgrounds will also be considered.
• Strong knowledge of probability and statistics (machine learning / NLP).
• Familiarity with language models such as BERT, GPT, and XLNet; NLP-related publications is a plus.
• Programming proficiency in Python.
• Experience working with large, complex datasets and building predictive models.
• Prior independent research experience in a data-driven environment.
• Outstanding analytics skills and attention to detail.
• Ability to clearly communicate complex and technical subject matters.
• Pragmatic, with a can-do attitude in approaching real-world investment problems.
• Results-driven mindset, ability to work in an ambiguous environment, and collaborate effectively within a team.

Locations & Compensation

Opportunities are available in Chicago and New York.

For applicants based in New York, California, or Illinois, the starting base pay range for this role is USD 14,000 to USD 20,000 per month. The actual base pay depends on factors such as relevant experience, business needs, and market demands. This role may also be eligible for bonus compensation and employee benefits.