Our client, a quant firm in Hong Kong is seeking a Research Engineering Developer to build and maintain a high-performance Python-based research platform, focusing on simulation engines, signal aggregation, and system optimization. The role requires advanced Python proficiency, experience with Docker/Kubernetes on AWS, and a background in quantitative finance for analyzing strategy performance.
Core Technical Skills (Must-Haves)
Expert Python:
Write clean, high-performance, production-ready code.
DevOps Expertise:
Deploy systems using Docker, Kubernetes (K8s), and AWS (EKS, S3, RDS).
STEM Degree:
Hold a Bachelor's degree in Computer Science, Engineering, or Math.
Primary Job Tasks (Daily Focus)
Platform Engineering:
Build a central quantitative research platform and simulation engines.
Library Development:
Create high-performance Python tools and libraries for researchers.
Infrastructure Management:
Manage containerized environments for scalable model deployment.
System Management & Optimization (Secondary Focus)
System Optimization:
Maximize computer speed, parallelization, and resource efficiency.
Signal Integration:
Build infrastructure to publish, group, and optimize trading signals.
Operations & Support:
Monitor daily production tasks and troubleshoot software issues.
Evaluation & Domain Knowledge (Supporting Skills)
Analytics Frameworks:
Develop tools to visualize backtest results and analyze risk metrics.
Finance Knowledge:
Understand asset classes like Equities, Derivatives, Fixed Income, and FX.
Soft Skills:
Stay self-motivated and collaborate effectively with research teams
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Core Technical Skills (Must-Haves)
Expert Python:
Write clean, high-performance, production-ready code.
DevOps Expertise:
Deploy systems using Docker, Kubernetes (K8s), and AWS (EKS, S3, RDS).
STEM Degree:
Hold a Bachelor's degree in Computer Science, Engineering, or Math.
Primary Job Tasks (Daily Focus)
Platform Engineering:
Build a central quantitative research platform and simulation engines.
Library Development:
Create high-performance Python tools and libraries for researchers.
Infrastructure Management:
Manage containerized environments for scalable model deployment.
System Management & Optimization (Secondary Focus)
System Optimization:
Maximize computer speed, parallelization, and resource efficiency.
Signal Integration:
Build infrastructure to publish, group, and optimize trading signals.
Operations & Support:
Monitor daily production tasks and troubleshoot software issues.
Evaluation & Domain Knowledge (Supporting Skills)
Analytics Frameworks:
Develop tools to visualize backtest results and analyze risk metrics.
Finance Knowledge:
Understand asset classes like Equities, Derivatives, Fixed Income, and FX.
Soft Skills:
Stay self-motivated and collaborate effectively with research teams
#J-18808-Ljbffr
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