Senior Quant Engineer

Create your best future as a Senior Quantitative Engineer!

Whats the role

Data Digital & AI (DDAI) is the engine driving digital transformation and innovation within Westpac Institutional Bank. Be part of the DDAI CTT team that transforms Westpacs Commodities and Trade Finance business by embedding digital data and AI capabilities endtoend covering analytics automation governance and risk so the business is modern scalable and futureread.

You will be building production grade quantitative and analytics systems that support trading pricing and risk decision-making across Commodities Trade and Transition. This role sits at the intersection of quantitative modelling software engineering and markets with a focus on turning high value quantitative ideas into reliable scalable production capabilities. There is scope to help shape the use of ML and AI over time applied pragmatically with strong engineering discipline and appropriate controls.

Key Responsibilities include:

• Quantitative & Analytics Engineering: Design and implement pricing risk and portfolio analytics used in real decision making.
• Production Ownership & Engineering Discipline: Contribute to disciplined testing release management monitoring and documentation.
• ML AI & Advanced Analytics: Contribute to the practical application of ML and GenAI (including LLM based systems) for analytics augmentation decision support and workflow automation.
• Markets & Collaboration: Apply analytics to pricing strategy risk management and execution analysis.

What do I need

This role requires a strong quantitative engineering background combining robust software development skills with deep analytical capability. The successful candidate will be comfortable working in dataintensive production environments and able to operate at senior level with flexibility for exceptional strength in either quantitative modelling or production engineering.

Additional skills and experience required include:

• Strong engineering capability in Python with proficiency in at least one of C Java or C#
• Advanced SQL skills and confidence working with largescale dataintensive workloads
• Solid grounding in applied mathematics statistics probability or optimisation
• Proven experience building scalable productiongrade analytics systems
• Background in quantitative development analytics engineering or frontoffice analytics within financial services
• It is desirable for you to have experience with cloud platforms preferably Azure and modern CI/CD practices
• You will ideally have exposure to machine learning tooling (such as PyTorch or TensorFlow) and LLM frameworks