Job Information
Trexquant Investment Quantitative Researcher - Summer 2025 Internship (USA) in Stamford, Connecticut
Please apply only if you are currently a junior in your bachelor's program or pursuing a master's or Ph.D. and eligible to start a full-time position the following winter or spring of 2026. If you do not qualify for this requirement and are early in your career, please apply directly to our Quantitative Researcher - Early Career role.
Join Trexquant, a pioneering quantitative investment fund established in 2014, as we shape the future of finance. Our team manages a multi-billion dollar global portfolio, delving into a diverse array of equities and liquid assets using cutting-edge machine learning techniques. Our founders and leaders, hailing from prestigious hedge funds, have cultivated an ecosystem ripe for innovation and unparalleled growth.
Responsibilities
As a Quantitative Research Intern, you will immerse yourself in a dynamic environment where data transforms into strategic trading opportunities:
Explore and Innovate: Dive deep into vast datasets to unearth signals that power systematic quantitative strategies.
Research and Implement: Stay at the forefront of academic research, applying the latest advancements in machine learning and quantitative finance.
Design and Enhance: Craft and refine features from emerging datasets to bolster the predictive capabilities of our existing models.
Analyze and Build: Leverage sophisticated machine learning tools to discover alpha and construct robust, market-neutral portfolios.
Requirements
Strong passion for machine learning and quantitative finance.
Strong problem-solving skills along with a creative approach towards developing market signals.
Ability to work effectively both as an individual and a team player.
Programming experience in any language, preferably Python.
Benefits
Monthly stipend and bonuses up to USD 3000 per month to exceptional performers.
Invaluable learning and networking opportunities with global hedge fund managers.
Access to proprietary technology platforms for exploring and converting ideas into signals that can be traded in the real world.
Mentoring and guidance from experienced quantitative researchers.
Weekly company provided lunches and other events throughout the program.