Develop and engineer robust, scalable, and automated applications that support index calculations, back-testing, performance attribution, and analytics frameworks
Job Summary
Develop and engineer robust, scalable, and automated applications that support index calculations, back-testing, performance attribution, and analytics frameworks.
Integrate, process, clean, and analyze diverse financial datasets, ensuring their appropriateness for production-grade applications.
Collaborate with Product, Research, and Operations teams to provide support and tools, transition prototype code, and extend the firm’s analytics and product offering.
Matching Summary
Develop and engineer robust, scalable, and automated applications that support index calculations, back-testing, performance attribution, and analytics frameworks.
Skills & Requirements
Must-have
Quantitative analysis and development
Software engineering best practices
Python and SQL programming
Data analytics libraries (numpy, pandas)
RESTful APIs and cloud-native solutions
Automated testing and CI/CD pipelines
Nice-to-have
Cross-asset cash and derivative instruments
Cloud development and deployment
JSON and XML models
Teamwork and innovation culture
Attention to detail and lateral thinking
Key Requirements
Minimum 2 years experience in quantitative analytics/R&D
Advanced degree (MSc or PhD) in scientific discipline