Jobs at Jump Trading Group

Source, map, evaluate, and promote alternative datasets for trading research. Responsibilities include identifying vendors, tracking market trends, vetting dataset quality and use cases, writing vendor summaries, maintaining data pipelines and catalogs, representing Jump with vendors, and communicating emerging opportunities. The role requires alternative-data market knowledge, vendor contacts, Excel proficiency, familiarity with privacy and compliance issues, and strong organization and writing skills.

Design, implement, test, and optimize C++ trading algorithms and market order execution systems. Collaborate with traders, quantitative researchers, and engineers to develop innovative strategies, improve trading platform performance, and optimize resource and hardware utilization. The role requires strong analytical, problem-solving, testing, communication, and teamwork skills, along with experience deploying large-scale data processing or modeling systems on high-performance computing clusters.

Lead a proprietary data analysis team supporting researchers, traders, and engineers. Coordinate priorities, define projects, ensure data quality, coach analysts, and personally solve complex data problems. Manage collection, tagging, cleaning, documentation, and validation of alternative, fundamental, market, and reference data. Partner with engineers to automate workflows while maintaining human review of AI-driven pipelines. Communicate findings and project status to technical and non-technical stakeholders.

Build and improve research and production infrastructure for quantitative trading. Develop Python and C++ systems, libraries, backend services, and workflow tooling for strategy research, testing, and deployment. Improve performance, algorithmic efficiency, scalability, and distributed compute capabilities while partnering with quantitative researchers and traders. Own projects through design, implementation, testing, rollout, and ongoing enhancement.

Quantitative Researchers analyze data sets, identify patterns, and develop predictive trading models while collaborating with various stakeholders in trading strategies.

Design, implement, maintain, and support large-scale HPC compute, storage, and monitoring systems. Build tooling, automate deployments, profile and debug application stacks, collaborate with researchers and vendors, participate in maintenance windows, provide on-call operational support, and improve documentation and testing infrastructure.

The role involves maintaining production servers, managing Python infrastructure, and solving operational issues in a quantitative trading environment.