Quantitative Researcher - Multi-Asset Arbitrage (Summer Internship)

Quantitative Researcher - Multi-Asset Arbitrage (Summer Internship)

BostonGreenwich

Posted Today

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 teams power our quantitative strategies and enhance our investment process.

As a QR Intern, you will go through a hands-on 10-week program designed to take your research abilities to the next level. You will have the opportunity to solve complex, real-world problems and make an impact by enhancing our investment and trading frameworks and strategies. Our program offers mentorship and collaboration with senior members of the team in addition to the opportunity to expand your network with the greater intern cohort. For this role, QR interns will be hired into one of our Multi-Asset Arbitrage teams.

Multi Asset Arbitrage Research interns are tasked with building, supporting, and integrating globally accessible quant trading infrastructure and interacting with Portfolio Managers and Quant Researchers to build requisite toolkits. 

Qualifications:

·   Bachelor's or Master's student graduating between Winter 2027 and Spring / Summer 2028 that is pursuing a degree in Mathematics, Statistics, Computer Science, or related quantitative field.

·   Programming proficiency in Python

·   Strong knowledge of probability and stats (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 is a plus

·   Outstanding analytics skills and attention to detail

·   Ability to clearly communicate complex and technical subject matters

·   Pragmatic and have a can-do attitude in approaching real-world investment problems

·   Results driven mindset, ability to work in an ambiguous environment, and work collaboratively within a team environment