- Company Name
- Jane Street
- Job Title
- Machine Learning Researcher
- Job Description
-
Job Title: Machine Learning Researcher
Role Summary:
A senior research engineer focused on designing, training, and deploying machine learning models to price, trade, and risk‑manage financial instruments. The role blends finance, software engineering, and research, driving end‑to‑end model development from data ingestion to production deployment.
Expectations:
- Lead end‑to‑end model development cycles, including data preprocessing, feature engineering, algorithm selection, hyper‑parameter tuning, and validation.
- Translate complex financial problems into actionable ML solutions and communicate findings to both technical and non‑technical stakeholders.
- Influence the research agenda, mentor junior researchers, and contribute to hiring and community building.
Key Responsibilities:
- Analyze large, high‑frequency trading datasets to uncover patterns and generate signal features.
- Build, test, and optimize predictive models (e.g., supervised, unsupervised, reinforcement learning) used in live trading systems.
- Implement scalable, reproducible training pipelines and production‑grade inference services.
- Continuously evaluate model performance, investigate drift, and iterate on architectures or feature sets.
- Collaborate with traders, quants, and engineers to integrate models into trading strategies and execution systems.
- Present research findings, publish internally and externally, and stay abreast of ML advances relevant to finance.
Required Skills:
- Deep expertise in machine learning frameworks (PyTorch, TensorFlow, JAX) and statistical modeling.
- Strong programming skills in Python, with proficiency in numeric libraries (NumPy, pandas, scikit‑learn).
- Experience with large‑scale data pipelines (SQL, Spark, Dask) and deployment tools (Docker, Kubernetes, MLflow).
- Familiarity with high‑performance computing, low‑latency execution, and financial data intricacies.
- Excellent analytical, problem‑solving, and communication abilities.
Required Education & Certifications:
- Ph.D. or Master’s degree in Machine Learning, Computer Science, Statistics, Quantitative Finance, or related field.
- Proven research track record (publications, patents, or significant project deliverables) in applied ML.
- Certifications in data science or ML (e.g., TensorFlow Developer, AWS Certified Machine Learning) are a plus.
New york city, United states
Hybrid
24-11-2025