Quantitative Researcher - Internship
New York, New York, United States
- Use the scientific method to develop sophisticated investment models and shape our insights into how the markets will behave
- Apply quantitative techniques like machine learning to a vast array of datasets
- Create and test complex investment ideas and partner with our engineers to test your theories
All the while, you’ll remain engaged in the academic community. As examples, you can:
- Join our reading circles to stay up to date on the latest research papers in your fields
- Attend academic seminars to learn from thought leaders from top universities
The internship program lasts 10 weeks in the summer and takes place at our Soho-based, New York City office. You will partner with an assigned mentor and work on a single project during the course of your time here, which will culminate in a final presentation at the conclusion of the program.
You should possess the following qualifications:
- Are pursuing a degree in a technical or quantitative disciplines, like statistics, mathematics, physics, electrical engineering, or computer science with approximately one year remaining in your programs (all levels welcome, from bachelor’s to doctorate)
- Demonstrate intermediate skills in at least one programming language (like C, C++, Java, or Python)
- Performed an in-depth research project, examining real-world data
- Are an independent thinker who can creatively approach data analysis and communicate complex ideas clearly
You don’t need a background in finance. It’s nice to have, but more than half of Two Sigma’s employees come from outside the finance industry. If you’ve got the quantitative skills, we can teach you the financial aspects of the job.
We are proud to be an equal opportunity workplace. We do not discriminate based upon race, religion, color, national origin, sex, sexual orientation, gender identity/expression, age, status as a protected veteran, status as an individual with a disability, or any other applicable legally protected characteristics.