Two Sigma is a leading quantitative investment management and trading firm that applies a scientific approach to investing. They are seeking a Data Scientist Intern who will independently research and develop hypotheses based on real-world datasets and collaborate with engineers and business stakeholders to explore and test theories.
Independently research and develop hypotheses based on diverse and unique real-world datasets
Conduct literature reviews to develop and apply cutting-edge methodologies for extracting meaningful signals from our vast data holdings
Partner with our engineers and business stakeholders to rigorously explore and 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
Qualification
Required
Are pursuing a degree in a technical or quantitative discipline, like chemistry, computer science, economics, statistics, or quantitative social science, with approximately one year remaining in your programs (all levels welcome, from bachelor's to doctorate)
Proficient in Python and SQL
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
Preferred
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
Benefits
Perks: Onsite gyms with laundry service, wellness activities, casual dress, snacks, game rooms
Hybrid Work Policy: Flexible in-office days with budget for home office setup
Two Sigma's technology-driven team streamlines the use of machine learning, distributed computing and research to guide its endeavors.