Job Description
Major Australian Bank | Sydney, NSW | Full-time
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About the Role
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This role is an prospect within a function driving digital transformation across an Institutional Bank. This role sits within a team transforming the bank's Commodities business.
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You'll build production-grade quantitative and analytics systems that support trading, pricing, and risk decision-making. The 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's scope to help shape the use of ML and AI over time, applied pragmatically with solid engineering discipline and appropriate controls.
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Key Responsibilities
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Quantitative & Analytics Engineering — Design and implement pricing, risk, and portfolio analytics used in real decision-making
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Production Ownership & Engineering Discipline — Contribute to disciplined testing, release management, monitoring, and documentation
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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
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Markets & Collaboration — Apply analytics to pricing strategy, risk management, and execution analysis
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What You'll Need
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This role requires a strong quantitative engineering background combining robust software development skills with deep analytical capability.



You'll be comfortable working in data-intensive production environments and able to operate at senior level, with flexibility for exceptional strength in either quantitative modelling or production engineering.
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Strong engineering capability in Python, with proficiency in at least one of C++, Java, or C#
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Advanced SQL skills and confidence working with large-scale, data-intensive workloads
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Solid grounding in applied mathematics, statistics, probability, or optimisation
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Proven experience building scalable, production-grade analytics systems
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Background in quantitative development, analytics engineering, or front-office analytics within financial services
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Desirable: experience with cloud platforms (preferably Azure) and modern CI/CD practices
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Desirable: exposure to ML tooling (e.g. PyTorch, TensorFlow) and LLM frameworks
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Why Apply
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Work on real, live problems with direct business impact across pricing, risk, and trading decisions
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Join a team embedding AI and modern engineering practices into one of Australia's largest financial institutions
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Flexible work arrangements and a genuine work/life balance, including a range of leave options
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Tailored learning and development opportunities
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Opportunities to get involved in community volunteering initiatives
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Competitive salary package and employee banking benefits
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📌 Senior Quantitative Engineer (New South Wales)
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