Quantitative Developer | Trading team

Reposted 9 Days Ago
Be an Early Applicant
Hiring Remotely in Hong Kong
Remote
Senior level
Financial Services
The Role
As a Quantitative Developer, you will develop and maintain research infrastructure, enhance trading systems, and collaborate on machine learning and portfolio optimization projects.
Summary Generated by Built In

Jump Trading Group is committed to world class research. We empower exceptional talents in Mathematics, Physics, and Computer Science to seek scientific boundaries, push through them, and apply cutting edge research to global financial markets. Our culture is unique. Constant innovation requires fearlessness, creativity, intellectual honesty, and a relentless competitive streak. We believe in winning together and unlocking unique individual talent by incenting collaboration and mutual respect. At Jump, research outcomes drive more than superior risk adjusted returns. We design, develop, and deploy technologies that change our world, fund start-ups across industries, and partner with leading global research organizations and universities to solve problems.

We’re expanding our successful global equity stat arb business with the build out of a new team of quantitative researchers and developers focused on developing mixed-frequency (low/mid) strategies based out of Hong Kong. As a quantitative developer, you will collaborate closely with the team’s researchers and engineers to architect, build, and maintain the team’s research infrastructure and production systems. You will work closely with the quantitative researchers on the team to create and improve research, develop and build out trading infrastructure, improve the scalability of the production systems while maintaining the production trading environment and troubleshooting problems, and developing software to automate and improve deployment, configuration, validation. As a new team, we’re looking for someone who enjoys open-ended problems and owning their solutions - you'll be a part of a cutting-edge team leveraging state-of-the-art technology and data, while working in a collaborative environment with opportunities for professional growth.

What you'll do:

  • You'll contribute to one or more of the following projects:
    • 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.
    • Microstructure research: Develop tools to enhance research on market microstructure, collaborating with researchers to generate and analyze key features.
    • Portfolio optimization: Design a portfolio optimization system to support comprehensive portfolio management strategies.
    • 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 You’ll Need:

  • 5+ year track record of solving challenging problems through coding with real metrics & impact in industry and/or academia.
  • Passion for building efficient, modular software to tackle challenging problems. Experience is a plus, but a strong desire to learn and grow is essential.
  • Strong software development skills in Python and/or C++.
  • Strong learning ability, intellectual curiosity, versatility, and originality combined with a pragmatic outlook.
  • Ability to reason through quantitative problems and communicate effectively with quantitative researchers.
  • Reliable and predictable availability to ensure smooth operations of production systems.
  • 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.

Skills Required

  • 5+ years of coding experience with real metrics
  • Strong software development skills in Python and/or C++
  • Over two years of experience with industrial grade codebases using C++

Jump Trading Group Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Jump Trading Group and has not been reviewed or approved by Jump Trading Group.

  • Career-Linked Recognition & Rewards Pay is considered very competitive for revenue‑adjacent and technical roles, with strong total packages when team performance is solid. Compensation structures align outcomes closely with impact, creating high satisfaction on strong desks.
  • Healthcare Strength Health coverage is described as comprehensive across medical, dental, and vision, with wellness programs and employer‑paid life/AD&D also highlighted. These offerings are portrayed as robust and compare favorably with similar employers.
  • Retirement Support A 401(k) with employer match is repeatedly noted, with mentions of a pension as well. Together these indicate strong retirement backing relative to many employers.

Jump Trading Group Insights

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The Company
HQ: Chicago, Illinois
1,488 Employees
Year Founded: 1999

What We Do

Jump Trading Group is committed to world class research. We empower exceptional talents in Mathematics, Physics, and Computer Science to seek scientific boundaries, push through them, and apply cutting edge research to global financial markets. Our culture is unique. Constant innovation requires fearlessness, creativity, intellectual honesty, and a relentless competitive streak. We believe in winning together and unlocking unique individual talent by incenting collaboration and mutual respect. At Jump, research outcomes drive more than superior risk adjusted returns. We design, develop, and deploy technologies that change our world, fund start-ups across industries, and partner with leading global research organizations and universities to solve problems.

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