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About the Role

This role offers an unparalleled educational experience, allowing interns to work alongside experienced Quantitative Researchers to learn about identifying market signals, analyzing data, building models, and creating trading strategies. The position emphasizes the integration of research, technology, and trading, providing access to vast data resources and computing power. The role is open to various statistical and machine learning techniques.

Responsibilities

Work side by side with experienced Quantitative Researchers.
Learn how to identify market signals.
Learn how to analyze large datasets.
Learn how to build and test models.
Learn how to create new trading strategies.
Gain a better understanding of the diverse array of challenges considered daily.
Learn how to think about experiment design.
Learn how to think about dataset generation.
Learn how to think about time series analysis.
Learn how to think about feature engineering.
Learn how to think about model building for financial datasets.
Participate in classes on the fundamentals of markets and trading.
Attend lunch seminars.
Engage in activities designed to understand the process of creating a new trading strategy.

Requirements

Able to apply logical and mathematical thinking to all kinds of problems.
Intellectually curious; eager to ask questions, admit mistakes, and learn new things.
A strong programmer who’s comfortable with Python.
An open-minded thinker and precise communicator.
Enjoys collaborating with colleagues from a wide range of backgrounds and areas of expertise.

Skills

Data science
Machine learning
Python programming
Logical thinking
Mathematical thinking
Communication
Collaboration

Experience Level

Internship
Research experience is a plus

Education Level

Current undergraduate or graduate students
Applicants who have already graduated

About the Company

At Jane Street, the lines between research, technology, and trading are intentionally blurry.
We don’t believe in “one-size-fits-all” modeling solutions; we are open to and excited about applying all different types of statistical and ML techniques, from linear models to deep learning, depending on what best fits a given problem.
If you’ve never thought about a career in finance, you’re in good company. Many of us were in the same position before working here.