1 day ago

Data Scientist Global Markets

Commonwealth Bank

Sydney

1 day ago

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Data Scientist role in Global Markets at Commonwealth Bank, leading applied AI solutions in Institutional Banking. Requires deep technical expertise in machine learning, generative AI, and agentic AI, with experience delivering solutions from inception to production. Hybrid role based in Sydney.

AI-enabledHybridFull-timeSeniorMachine LearningGenerative AI

Data Scientist Global Markets

Apply

AI-enabledHybridFull-timeSeniorMachine Learning

Salary

Not specified

Work Location

Sydney, New South Wales, Australia, AU

Work Model

Hybrid

Employment Type

Full-time

Experience Level

Mid-Senior level

Core Qualifications

Technical (Must-have)

Machine LearningGenerative AIAgentic AIPythonSQLCloud PlatformsAdvanced ModellingModel Risk ManagementData QualityExplainabilityDrift Monitoring

Soft Skills

LeadershipCoachingMentoringCommunicationCommercial JudgementStakeholder ManagementProblem Solving

Key Responsibilities

•Lead AI initiatives end to end, from problem definition through production deployment and monitoring.
•Set technical direction while staying hands-on.
•Translate complex commercial and markets problems into scalable machine learning and agentic AI solutions.
•Establish and hold modelling, validation, governance and monitoring practices in a regulated environment.
•Partner with business, engineering, risk and governance teams to deliver safe and responsible outcomes.
•Develop data scientists and graduates through coaching, mentoring and technical leadership.
•Drive integration between AI delivery, engineering practice and business process.
•Influence senior stakeholders by connecting technical decisions to commercial value and P&L.
•Design commercially viable delivery patterns.
•Apply strong model-risk judgement to AI solutions.

Data ScienceAIMachine LearningGlobal MarketsInstitutional BankingFinancial ServicesHybridSydneyLeadership

Key Responsibilities

•Lead AI initiatives end to end, from problem definition through production deployment and monitoring.

•Set technical direction while staying hands-on.

•Translate complex commercial and markets problems into scalable machine learning and agentic AI solutions.

•Establish and hold modelling, validation, governance and monitoring practices in a regulated environment.

•Partner with business, engineering, risk and governance teams to deliver safe and responsible outcomes.

•Develop data scientists and graduates through coaching, mentoring and technical leadership.

•Drive integration between AI delivery, engineering practice and business process.

•Influence senior stakeholders by connecting technical decisions to commercial value and P&L.

•Design commercially viable delivery patterns.

•Apply strong model-risk judgement to AI solutions.