WorldQuant
Quantitative Developer
An early-career Quantitative Developer role focused on building automation and tools to support business workflows, involving Python/C++ programming, operational tooling, and collaboration within a systematic investing environment.
Responsibilities
- Monitor production systems, scheduled jobs, data processes, and automated workflows; identify and bring up issues appropriately
- Investigate technical issues across applications, data processes, and infrastructure; contribute well-tested fixes under guidance
- Design, build, and maintain internal tools, automation, interfaces, and services that improve business workflows
- Improve system reliability, observability, documentation, and team productivity
- Collaborate with engineers and stakeholders to understand requirements and translate them into practical technical solutions
- Contribute to code reviews, testing, release validation, and user documentation
- Assist the on-call team with incident triage, diagnostics, communication, validation, and follow-up activities
- Identify repetitive manual tasks and build automation to reduce operational overhead
Requirements
- Bachelor's/ Master's degree or equivalent experience in Computer Science, Engineering, or a related field
- Solid practical experience in Python and/or C++
- Good knowledge of Bash scripting and Linux environments
- Familiarity with version control systems such as Git
- Interest in automation, production systems, operational tooling, and reliable software delivery
- Strong analytical and logical thinking, with a methodical approach to solving problems
- Meticulous, with a high standard for accuracy, quality, and reliability
- A self-starter who takes ownership of assigned work and knows when to seek guidance or escalate
- Comfortable handling multiple tasks and priorities in a fast-paced environment
- Able to learn quickly and adapt to unfamiliar technologies and complex systems
- Effective and concise communicator in English, both written and verbal
- Solid understanding of Claude or other LLM tools, and an understanding of how to apply them effectively across debugging, problem analysis, solution design, testing, and documentation
- Uses LLM tools with sound judgment and critical thinking — as a force multiplier for quality, speed, and clarity, not as a substitute for engineering discipline
- Brings a continuous-improvement approach and contributes to improving team processes, documentation, and automation
Skills
- Python
- C++
- Bash scripting
- Linux
- Git
- Automation
- Operational tooling
- Employer posted
- Last checked