Quantitative Research Intern

DRW•Chicago, NY

2d•Onsite

About The Position

As a Quantitative Research Intern, you will have the opportunity to solve challenging problems arising in a trading environment while utilizing the latest statistical scientific algorithms, machine learning techniques, and derivatives pricing theory. The teams focus on non-latency sensitive investment opportunities and multi-asset class derivatives strategies across geographies. Our teams emphasize cutting-edge innovative scientific research and collaboration, allowing you to gain a deeper understanding of quantitative trading. You will find great minds with diverse backgrounds, who are passionate about cultivating new ideas and exploring ways to bring them to life. You will use the team’s custom research infrastructure for simulation, back-testing, and validation of the proposed models. While your days will have you engrossed with complex technology projects, your evenings will be spent exploring the city with organized social events to truly discover what it’s like to live and work in Chicago or New York City.

Requirements

Pursuing a Bachelor’s, Master’s or PhD in a technical discipline with a focus on Statistics, Optimization, Machine Learning, Artificial Intelligence, Quantitative Finance or related fields graduating between December 2027 and August 2028
Proficiency in Python programming experience using the Python machine learning stack: numpy, pandas, scikit-learn, etc.
Proficient programming skills with experience exploring large datasets
Strong analytical and problem-solving skills including a solid foundation of statistics knowledge
Working knowledge of probability theory, stochastic calculus and numerical algorithms such as finite differences, Monte Carlo simulation, etc.
Excellent written and verbal communication skills to report research results as well as methodologies

Nice To Haves

Some exposure to Natural Language Processing and/or High-Performance Computing is a plus
Been published in a top tier journal focusing on Natural Language Processing or High-Performance Computing

Responsibilities

Create practical solutions to problems presented in the trading environment on either a systematic equity trading desk or a fixed income options desk
Conduct statistical analysis of market data, historical trends, and relationships across multiple asset classes
Formulate and apply mathematical modeling, quantitative methods and machine learning techniques to identify and capture trading opportunities
Work closely with traders and researchers to build and refine research infrastructure and tools