Quantitative Researcher - 2027 Summer Internship

Quantitative Researcher - 2027 Summer Internship

Internship 22500 - 27500 £ / year (est.) On-site
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At a Glance

  • Tasks: Work alongside experienced researchers to analyse data and develop trading strategies.
  • Company: Join Jane Street, a leader in finance with a focus on innovation.
  • Benefits: Gain hands-on experience, mentorship, and access to cutting-edge technology.
  • Other info: Perfect for undergraduates or graduates looking to explore finance careers.
  • Why this job: Dive into the world of finance and data science while making a real impact.
  • Qualifications: Strong programming skills in Python and a passion for learning.

The predicted salary is between 22500 - 27500 £ per year.

Our goals are to give you a real sense of what it's like to work as a Quantitative Researcher at Jane Street while also providing a truly unparalleled educational experience. You'll work side by side with our experienced Quantitative Researchers to learn how we identify market signals, analyse large datasets, build and test models, and create new trading strategies.

At Jane Street, the lines between research, technology, and trading are intentionally blurry, and you’ll have access to petabytes of data, a computing cluster with hundreds of thousands of cores, and a growing GPU cluster containing tens of thousands of high-end GPUs. We don’t believe in “one-size-fits-all” modelling 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.

You'll spend the bulk of your internship working closely with full-time researchers on projects drawn from their own work. You'll gain a better understanding of the diverse array of challenges we consider every day, learning how we think about experiment design, dataset generation, time series analysis, feature engineering, and model building for financial datasets. Your day-to-day project work will be complemented by classes on the broader fundamentals of markets and trading, lunch seminars, and activities designed to help you understand the entire process of creating a new trading strategy, from initial exploration to finding and productionizing a signal.

About you

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. Most candidates will have experience with data science or machine learning, but ultimately, we're more interested in how you think and learn than what you currently know. You should be:

  • 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 who enjoys collaborating with colleagues from a wide range of backgrounds and areas of expertise

Most interns are current undergraduate or graduate students, but we also welcome applicants who have already graduated and are considering a new career in finance. Research experience is a plus.

If you'd like to learn more, you can read about our interview process, meet some of the team, and learn more about Jane Street's internship program on our website.

Quantitative Researcher - 2027 Summer Internship employer: Tum International Gmbh

The D. E. Shaw group is an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration in the heart of London. Interns benefit from hands-on experience in trading and analytics, with ample opportunities for professional growth and mentorship from industry leaders, all while being part of a forward-thinking firm at the forefront of finance and technology.

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Contact Details:

Tum International Gmbh Recruitment Team

We think you need these skills to ace Quantitative Researcher - 2027 Summer Internship

Data Analysis
Machine Learning
Statistical Techniques
Model Building
Python Programming
Logical Thinking
Mathematical Thinking