Jane Street

About the Company

Jane Street is a quantitative trading firm with offices in New York, London, Hong Kong, Singapore, and Amsterdam. We are always recruiting top candidates and we invest heavily in teaching and training. The environment at Jane Street is open, informal, intellectual, and fun. People grow into long careers here because there are always new and interesting problems to solve, systems to build, and theories to test.

More than twenty years after our founding, it still feels like we’re just getting started.

Jane Street does not offer any services to individual investors: https://www.janestreet.com/fraud-and-impersonation-warnings/

Listed Jobs

Company Name

Jane Street

Job Title

Machine Learning Researcher

Job Description

Job Title: Machine Learning Researcher Role Summary: Independently design, develop, and evaluate machine learning models, strategies, and systems that support pricing and trading of diverse financial instruments. Lead experimentation, feature engineering, and model tuning in a fast‑moving trading environment, while mentoring peers and establishing ML objectives across the organization. Expectations: Deliver production‑ready models and trading strategies that achieve measurable trading performance gains. Share expertise by publishing findings, presenting to stakeholders, coaching junior researchers, and influencing company‑wide ML practices. Demonstrate strong communication skills, effective problem‑solving, and an ability to balance technical innovation with operational reliability. Key Responsibilities: - Analyze large financial datasets to extract actionable insights for modeling. - Build, test, and deploy machine learning models and trading algorithms. - Experiment with feature transformations, model architectures, and hyperparameters to optimize inference quality and robustness. - Collaborate with quantitative analysts and traders to understand domain problems and translate them into model solutions. - Mentor and onboard new researchers, establishing best practices and coding standards. - Represent the research team at industry conferences and contribute to external publications. - Define and track performance metrics and quality benchmarks for ML systems. - Assist in hiring decisions for research and engineering roles. Required Skills: - Advanced knowledge of supervised/unsupervised learning, deep learning, reinforcement learning, and statistical modeling. - Proficiency in programming languages such as Python or C++ and ML libraries (TensorFlow, PyTorch, scikit‑learn). - Experience with large‑scale data pipelines, feature engineering, and model deployment in production environments. - Strong analytical and quantitative reasoning with a solid grasp of financial markets. - Excellent written and verbal communication abilities. - Ability to work independently while collaborating across multidisciplinary teams. Required Education & Certifications: - PhD or Master’s degree in Computer Science, Applied Mathematics, Statistics, Finance, or related field; or equivalent professional experience. - Proven track record of research publications or substantial ML project experience in industry or academia.

New york city, United states

Hybrid

23-02-2026