Quantitative Developer | Trading Team

Jump Trading Jump Trading · Quant · Hong Kong · Front Office

Quantitative Developer role at Jump Trading focused on building and maintaining research infrastructure and production systems for a new global equity stat arb business. Responsibilities include machine learning development, microstructure research, portfolio optimization, and data pipeline management. Requires strong software development skills in Python/C++ and experience with challenging problems.

What you'd actually do

  1. Machine learning development: Build the team's proprietary end-to-end machine learning pipeline. Work extensively with quantitative researchers to understand requirements and constraints, implement proprietary ML features and algorithms, and continuously improve model design, tools, and infrastructure.
  2. Microstructure research: Develop tools to enhance research on market microstructure, collaborating with researchers to generate and analyze key features.
  3. Portfolio optimization: Design a portfolio optimization system to support comprehensive portfolio management strategies.
  4. Data Pipeline and System Management: Engage in full-cycle development, including research, coding, testing, and deploying systems into production. Provide direct support to end users, troubleshoot issues, and manage system upgrades.

Skills

Required

  • Python
  • C++
  • quantitative problem solving
  • software development

Nice to have

  • high-performance computing (HPC)
  • distributed large-scale model training
  • market microstructure research
  • portfolio optimization
  • industrial grade codebases

What the JD emphasized

  • 5+ year track record of solving challenging problems through coding with real metrics & impact in industry and/or academia
  • Strong software development skills in Python and/or C++
  • Over two years of experience working with industrial grade codebases using compiled languages such as C++ is advantageous
  • Familiarity with high-performance computing (HPC) and distributed large-scale model training is a plus

Other signals

  • quantitative researchers
  • machine learning development
  • proprietary ML features and algorithms
  • model design, tools, and infrastructure
  • large-scale model training