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 to build deep learning models for trading strategies, leveraging large-scale GPU clusters and novel techniques to address challenges in nonstationary datasets and multi-agent environments. The role involves training next-generation models, understanding new markets, and contributing to hiring and knowledge sharing.

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 tackling challenges like large models, nonstationary datasets, and multi-agent environments, requiring novel techniques. Researchers collaborate closely with engineers and traders, diving into market data, hyperparameter tuning, distributed training, and model behavior in production. The position requires in-depth knowledge of ML, including LLMs, image models, RL agents, recommendation systems, and classical ML, to shape the future of ML at Jane Street. Responsibilities include training next-generation models, building fundamental understanding for new markets, hiring, attending conferences, and teaching teammates.

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.

Machine Learning Researcher to build deep learning models for trading strategies, leveraging a large GPU cluster and tackling challenges like large models, nonstationary datasets, and multi-agent environments. The role involves training models, architecting systems, and researching novel techniques across various ML domains (LLMs, image models, RL agents, recommendation systems, classical ML). Responsibilities include training next-gen models, building fundamental understanding, hiring, attending conferences, and teaching teammates.

Research role focused on building deep learning models for trading strategies, leveraging a large GPU cluster. The role involves training models, architecting systems, and understanding market data in a competitive multi-agent environment, pushing for novel techniques across various ML domains like LLMs, image models, RL agents, and recommendation systems.

Research role focused on applied research in weather prediction, embedded within a commodities trading desk. Requires strong programming skills (Python), expertise in atmospheric science topics, and experience with AI models. The role involves challenging the limits of atmospheric predictability and exploring new research directions.

Applied research role on a weather team, embedded within a commodities trading desk, focusing on atmospheric predictability challenges. Requires strong Python programming and expertise in atmospheric science topics, with AI model experience preferred.

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.

Jane Street is seeking Quantitative Researchers to build models and systems for pricing and trading financial instruments. The role involves working with large datasets and advanced computing infrastructure, applying various statistical and ML techniques, and collaborating closely with engineers and traders. The focus is on developing actionable strategies based on data analysis and model building.

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 working with large datasets and advanced computing infrastructure, applying various statistical and ML techniques, and collaborating closely with engineers and traders. Success requires a curious, logical, and programming-proficient individual who can adapt findings into actionable strategies.

Jane Street is seeking an experienced Machine Learning Educator to develop and maintain their ML educational programs. This role involves teaching general ML, AI assistants, internal training stacks, and performance reasoning. The educator will also write code for ML research, mentor other teachers, and develop curricula. Experience teaching ML in a university or industry setting is required.

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.

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 closely with engineers and traders, working with large datasets and GPU clusters. The role is open to various statistical and machine learning techniques, emphasizing curiosity, problem-solving, and adaptability.

Jane Street is seeking Quantitative Researchers to 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 will collaborate with engineers and traders, working with large datasets and a significant GPU cluster. The position is open to various statistical and machine learning techniques, emphasizing curiosity and the ability to integrate findings into actionable trading strategies.

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 Natural Gas Analyst/Trader to research and develop new strategies that integrate fundamental analysis with quantitative trading approaches within the natural gas market.

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. The role involves close collaboration with research and technology, utilizing large-scale computing resources and applying various statistical and ML techniques, including deep learning.

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.

Experienced Macro Analyst to provide macroeconomic and geopolitical insights to global trading and research teams, focusing on developing well-reasoned views and expanding trading opportunities. Responsibilities include macro updates, quantitative analysis, aggregating research, and deep dives into specific topics.

Seeking a Statistical Arbitrage Research Analyst to apply math and statistical methods to develop trading strategies across various asset classes. Role involves analyzing diverse datasets, assessing data quality, feature engineering, and collaborating with a team. Experience in quantitative research and statistical/ML modeling is preferred.

Experienced FTR trader to trade congestion products, conduct research, and design trading strategies in multiple ISO/RTOs. Requires strong market knowledge, analytical skills, and experience with strategy lifecycle and risk management.

Research internships in Tools and Compilers group focusing on improving OCaml, including type systems, optimizers, and toolchain enhancements. Projects involve applying state-of-the-art research to a production codebase.

Research internship in Jane Street's Tools and Compilers group, focusing on improving OCaml. Projects involve type systems, superoptimization, and compiler testing, applying state-of-the-art research to a production codebase.