Lead, Quant Engineer

In this role, you will build and evolve platform capabilities and data infrastructure that support the Quantitative Modelling and Strategies (QMS) team. You will collaborate with researchers and tech groups to deliver scalable platforms enabling investment analytics. You’ll apply Python engineering, data engineering, and distributed computing to create enterprise-wide tools for quantitative research. Expect a hands-on impact on architecture, automation, and operational excellence within a global asset management context. This position offers the chance to shape how quant teams operate and to work at the intersection of technology and finance.

• Private Medical Insurance
• Annual Leave 25–28 days
• Retirement Savings Plan with company contribution
• Life Assurance & Income Protection

• Design and develop platform capabilities and tooling using Python
• Build and support data platforms, quantitative libraries, and distributed infrastructure
• Partner with researchers and tech teams to align capabilities with business needs
• Contribute to architecture, code reviews, testing, performance optimization, and operational excellence
• Drive automation and engineering best practices to enable scalable analytics

• Bachelor in Computer Science
• Significant experience delivering enterprise-scale software, analytics, and data platforms
• Deep expertise in Python software development
• Experience in data engineering, distributed computing, and large-scale data processing
• Experience building quantitative analytics, risk management, portfolio management, or quant platforms
• Experience partnering with quantitative researchers, investment teams, and technology organizations
• Understanding of fixed income, credit, asset management, or broader financial markets
• Strong analytical, problem-solving, and communication skills with a collaborative mindset

• collaborative mindset
• strong communication
• problem-solving ability
• Python
• data engineering
• distributed computing