Quantitative Researcher
Jane Street· Trading, Research, and Machine Learning
Hybrid (Hong Kong)not specifiedPosted 1mo ago
About the role
Quantitative Researchers to help build models, strategies, and systems that price and trade financial instruments. Work with researchers, engineers, and traders to design experiments, generate datasets, perform time series analysis, feature engineering, and model building for financial data. Collaboration across teams and hands-on work with large-scale data and compute resources.
Responsibilities
- Build models, strategies, and systems that price and trade financial instruments
- Work with experienced researchers to learn experiment design, dataset generation, time series analysis, feature engineering, and model building for financial datasets
- Collaborate with researchers, engineers, and traders to train models, architect systems, and run trading strategies
- Explore a variety of statistical and ML techniques (from linear models to deep learning) to fit problems and adapt findings into actionable strategies
- Diver deeper into market data, tuning hyperparameters, debugging distributed training performance, and studying model behavior in production
Qualifications
- Able to apply logical and mathematical thinking to problems
- Intellectually curious; eager to ask questions, admit mistakes, and learn new things
- Strong programmer comfortable with Python
- Open-minded thinker and precise communicator who collaborates with diverse backgrounds
- Fluent in English
- PhD or other research experience is a plus
- Most candidates will have experience with data science or machine learning, but emphasis is on thinking/learning ability over current knowledge
Skills
Required:Mathematical thinkingPython
Benefits
- Jane Street is an Equal Opportunity Employer
Last updated Oct 25, 2026. Interested? Apply on the company site.
About Jane Street
SIX
Jane Street is a quantitative trading firm and liquidity provider with a unique focus on technology and collaborative problem solving.
Machine learningquantitative tradingtechnologyresearch-drivenglobal marketsinternshipseventsprograms
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