Quantitative Researcher

Benefits

Parental leave

Not verified

Non-birth-parent leave

Not verified

Family-building benefits

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

Mental health support

Not verified

Relocation assistance

Not verified

Childcare support

Not verified

Learning budget

Not verified

Verification

Not verified

Salary

Not verified

401(k) match

Not verified

Was this benefit information wrong? Tell us.

Schedule

Shift type

Not verified

Weekend work

Not verified

Application

Cover letter

Not verified

Assessment

Not verified

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

Read the full description at job-boards.greenhouse.io. FewerJobs shows a source-linked preview and links to the original posting.