Quantitative Researcher - Systematic Strategies (Summer Internship - PhD)

Quant Research Intern (QR Intern) — 10-Week Program

At BAM, our Researchers collaborate across all asset classes, delivering quantitative practices in areas such as risk management, big data analysis, AI, LLMs, 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 work on complex, real-world problems and help improve our investment and trading frameworks and strategies. The program includes mentorship and collaboration with senior team members, along with the opportunity to expand your network through the broader intern cohort.

QR interns are hired into teams including: Systematic, Multi-Asset Arbitrage, Risk, and Portfolio Construction.

Internship Opportunity Areas

• 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; collaborate with Portfolio Managers and Quant Researchers to develop required toolkits.
• Alpha Capture Research: Develop alphas using LLM and machine learning methods to enhance trading strategies within a L/S Equity investment team.
• Quant Risk Management: Work with Senior Researchers and Risk Managers to improve framework models and conduct research analysis of the investment process, providing insights into portfolio construction and risk exposures.
• Portfolio Construction Research: Conduct factor model research and build tools essential to equity factor research used across the firm.

Qualifications

• PhD student graduating between Winter 2027 and Spring/Summer 2028, pursuing a degree in Mathematics, Statistics, Computer Science, or a related quantitative field.
• Programming proficiency in Python.
• Strong knowledge of probability and statistics (ML/NLP).
• Experience working with large, complex datasets and building predictive models.
• Prior independent research experience in a data-driven environment.
• Familiarity with language models such as BERT, GPT, and XLNet, and NLP-related publications (plus).
• Outstanding analytics skills and attention to detail.
• Ability to clearly communicate complex and technical topics.
• Pragmatic approach and a can-do attitude toward real-world investment problems.
• Results-driven mindset; ability to work in an ambiguous environment and collaborate within a team.

Compensation (NY, CA, IL Applicants)

For applicants based in New York, California, and Illinois, the starting base pay range for this role is between USD 15,000 and USD 25,000 per month. The actual base pay depends on several factors, including relevant experience, business needs, and market demands. This role may also be eligible for bonus compensation and employee benefits.