Quantitative Researcher

Posted 4 Days Ago
Be an Early Applicant
New York, NY
Internship
Financial Services
The Role
As a Quantitative Research intern, you will collaborate with full-time employees on projects involving market signal identification, large dataset analysis, model building, and trading strategy development. You will tackle complex problems utilizing various statistical and machine learning techniques, while gaining insights into research challenges related to financial datasets.
Summary Generated by Built In

About the program

Our goal is to give you a real sense of what it’s like to work at Jane Street full time. As an intern, you are paired with full-time employees who act as mentors, collaborating with you on real-world projects we actually need done. Over the course of the summer, you will explore ways to approach and solve exciting problems through fun and challenging classes, interactive sessions, and group discussions — and then you will have the chance to put those lessons to practical use. At the end of the workday, we often host guest speakers and offer a variety of social events to take part in.

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. If you have a curious mind, a collaborative spirit, and a passion for solving interesting problems, we have a feeling you’ll fit right in.

About the position

As a Quantitative Research intern, you’ll work side by side with full-timers to learn how we identify market signals, analyze large datasets, build and test models, and create new trading strategies. 

At Jane Street, we blur the lines between trading and research, fostering a fluid environment where teams work in a tight loop to solve complex problems. 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.

Our advanced proprietary trading models are the backbone of our operation, enabling us to identify profitable trading opportunities across hundreds of thousands of financial products, in over 200 trading venues globally. We utilize petabytes of data, our computing cluster with hundreds of thousands of cores, and our growing GPU cluster containing thousands of A/H100s to develop trading strategies in adversarial markets that evolve every day.

During the program you’ll focus on two projects, mentored closely by the key stakeholders who’ve worked on them. You may conduct a study of some new or existing dataset, build new tools that support the firm’s research, or consider big-picture questions that we’re still trying to figure out. The problems we work on rarely have clean, definitive answers — and they often require insights from colleagues across the firm with different areas of expertise. 

You’ll gain a better understanding of the diverse array of research challenges we consider every day, learning how we think about 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.

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.

If you’d like to learn more, you can read about our interview process and meet some of our newest hires.

About you

We don’t expect you to have a background in finance or any other specific field — we’re looking for smart, ambitious people who enjoy solving challenging problems. 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
  • Research experience a plus

If you're a recruiting agency and want to partner with us, please reach out to [email protected]

Top Skills

Python
The Company
HQ: New York, NY
1,390 Employees
On-site Workplace
Year Founded: 2000

What We Do

Jane Street works differently. As a liquidity provider and market maker, we trade on more than 200 trading venues across 45 countries and help form the backbone of global markets. Our approach is rooted in technology and rigorous quantitative analysis, but our success is driven by our people.

Our bright, beautiful offices in the heart of New York, London, Hong Kong, and Amsterdam are open and buzzing with conversation. We come from many backgrounds and encourage travel between offices to share perspectives. Some of our best ideas come from bumping into a visiting colleague at the office coffee bar.

Markets move fast. Staying competitive as we’ve grown has required constant invention—of new trading strategies, technology, and processes. We’ve found this is easier when you hire humble, kind people. They tend to help each other, and prioritize teamwork over titles.

We invest heavily in teaching and training. There’s a library and a classroom in every office, because deepening your understanding of something is considered real work. Guest lectures, classes, and conferences round out the intellectual exchanges that happen every day.

People grow into long careers at Jane Street because there are always new and interesting problems to solve, systems to build, and theories to test. More than twenty years after our founding, it still feels like we’re just getting started.

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