Quantitative Researcher

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

• Fertility benefits: Not verified
• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

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Learning budget

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Verification

Not verified checked Jun 7, 2026

Salary

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401(k) match

Reported from DOL Form 5500 industry filing (not employer-specific)

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Market context

U.S. role benchmark (BLS OEWS)

$111,944 U.S. median for this role

Projected growth (BLS Employment Projections)

+13.7% - Much faster than average

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Data From the posting source checked Jun 20, 2026

Seniority

Mid From the posting source checked Jun 20, 2026

Schedule

Shift type

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Weekend work

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Company

Company stage

Public-company From the posting source checked Jun 20, 2026

Application

Cover letter

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Assessment

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Deadline

Not stated

Where they hire

State eligibility is not yet verified.

About this role

Quantitative Researcher Hong Kong, Hong Kong 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. As our strategies grow more sophisticated, close collaboration is essential for continuing to push the boundaries of what's possible. We work with 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

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