Jane Street

Jane Street is seeking a Machine Learning Researcher to work on projects combining novel ML ideas with systematic trading strategies. The role involves end-to-end studies, exploring new modeling paradigms, and applying state-of-the-art techniques to challenging problems in finance, utilizing large-scale data and computing resources. The position is for a PhD student or postdoc with empirical ML research experience, strong logical and mathematical thinking, and Python implementation skills.

Machine Learning Researcher at Jane Street to build deep learning models for trading strategies, leveraging large-scale GPU clusters and tackling challenges like large models, nonstationary datasets, and multi-agent environments. The role involves training next-generation models, developing fundamental understanding for new markets, and contributing to hiring and knowledge sharing.

Machine Learning Researcher to build deep learning models for trading strategies, supported by a large GPU cluster. The role involves training models, architecting systems, and studying model behavior in production, with a focus on novel techniques for challenges like large models, nonstationary datasets, and multi-agent environments. Responsibilities include hiring, attending conferences, and teaching.

Quantitative Researcher role at Jane Street focusing on identifying market signals, analyzing data, building and testing models, and creating trading strategies. The role involves close collaboration with experienced researchers, working with large datasets and GPU clusters, and applying various statistical and ML techniques. Interns will work on projects, learn about experiment design, dataset generation, time series analysis, feature engineering, and model building for financial datasets, complemented by classes on markets and trading.

Quantitative Researchers at Jane Street build models, strategies, and systems for pricing and trading financial instruments. The role involves working with experienced researchers on experiment design, dataset generation, time series analysis, feature engineering, and model building for financial datasets. Researchers collaborate closely with engineers and traders, utilizing large-scale data and computing resources. The role is open to various ML techniques, from linear models to deep learning, and emphasizes curiosity, logical thinking, strong programming skills (Python), and collaboration.

Quantitative Researchers at Jane Street build models, strategies, and systems for pricing and trading financial instruments. The role involves applying expertise in experiment design, dataset generation, time series analysis, feature engineering, and model building to financial datasets. Researchers collaborate with engineers and traders, working with large datasets and GPU clusters. The position is open to various statistical and machine learning techniques, including deep learning, and requires strong programming skills in Python and a curious, collaborative mindset.

This role involves quantitative trading, focusing on analyzing market signals, developing predictive models, and constructing quantitative strategies using statistical and ML techniques. It emphasizes learning and applying these methods to financial data, with opportunities to build tools and answer complex questions.

Seeking an experienced Macro Analyst to enhance global trading strategies with quantitative and fundamental analysis, focusing on global macro topics and expanding trading opportunities.

Quantitative traders at Jane Street identify market signals, analyze and execute strategies, construct quantitative models, conduct statistical analyses, build algorithmic trading systems, and manage risk. They work with large datasets and leverage various statistical and ML techniques, from linear models to deep learning, in a collaborative environment.