ApplySarthiQuantitative Researcher
Jane Street
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This role on the market
292 open quantitative roles across 49 companies are on ApplySarthi right now, most of them in Mumbai (8), Delhi NCR (4), Hyderabad (2).
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What quantitative roles keep asking for: Python (80%), Machine learning (46%), C++ (33%), SQL (27%), R (18%) — counted across their open postings here.
Quantitative Researcher jobs in the United States · Quantitative Researcher jobs in New York · Deep learning jobs · Machine learning jobs · Python jobs
Jane Street has 217 open roles listed here.
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Counted across 14 company job boards, updated as roles open and close.
Preparing for this interview
Interviews for quantitative roles keep coming back to Python, Machine learning, C++, SQL. Practise those questions before you sit with Jane Street.
Questions you are likely to be asked
- Why do you want to join Jane Street?
- What is your experience with Deep learning? Tell me one thing you learned the hard way.
- Tell me about yourself, and why this role is the right next step.
- Tell me about a problem you solved at work that you are proud of.
- Tell me about a time you disagreed with your manager. What happened?
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Practise the Quantitative Researcher at Jane Street interview free →About the Position
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, analyze 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” 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.
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 and meet some of the team. Learn more about Jane Street’s internship program here.
If you're a recruiting agency and want to partner with us, please reach out to agency-partnerships@janestreet.com.
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Listed on greenhouse · posted 2026-07-06. ApplySarthi collects openings and links to application pages; the role is advertised by Jane Street, not by us.