The board
- Where
- Chicago, New York City
- Posted
- Jul 13
Our formula for success is to hire exceptional people, encourage their ideas and reward their results.
As a Quantitative Research Intern you will have an 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.
What you'd do
- 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
- Are 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.
- Some exposure to Natural Language Processing and/or High-Performance Computing is a plus