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Develop machine learning and AI solutions to improve customer experiences in home lending, working across the full data science lifecycle from problem framing through deployment. You'll need strong foundations in statistics and machine learning with demonstrated experience on complex commercial problems, plus practical expertise in Python, SQL, supervised learning, and agentic or generative AI applications. The role involves designing experiments, building predictive models, and balancing technical performance with responsible data use and business value.

Written from this posting by Neural Jobs AI. The full description is below.

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Job Description

Do Work That Matters

Join a Growth squad focused on using data, machine learning and emerging AI capabilities to improve customer experiences within home lending.

As a Data Scientist, you’ll develop machine learning and agentic AI solutions that help the business better understand customer needs and support more relevant, informed customer conversations. You’ll work with complex datasets to uncover meaningful patterns, develop predictive models and create intelligent applications that turn data into practical insights.

You’ll take ownership across the data science lifecycle, from framing the business problem and evaluating possible approaches through to experimentation, model or agent development, validation, deployment and monitoring. You’ll balance technical performance with responsible data use, operational feasibility and commercial value, selecting the most appropriate solution rather than defaulting to the most complex approach.


See yourself in our team

Join a team where you’ll have a positive impact on customers’ lives, strengthen local communities, and build a rewarding career.


In this role, you will:

  • Identify and optimise customer cohorts for home lending opportunities, leveraging a mix of advanced analytics, data science and predictive modelling to drive targeted customer engagement.
  • Design, execute and measure experiments to evaluate the effectiveness of customer propositions, using statistical analysis and experimentation frameworks to generate actionable insights and improve outcomes.
  • Develop and apply AI-powered solutions, including GenAI and agentic capabilities, to enhance customer communications, improve personalisation and create seamless customer experiences across the lending journey.
  • Determine whether a problem is best addressed through machine learning, statistical techniques, rules, an agentic application or a combination of approaches.
  • Develop robust experimentation and evaluation frameworks that assess technical performance, reliability, customer relevance and commercial impact.

We’re interested in hearing from people who:

Bring strong foundations in statistics, mathematics and machine learning, together with demonstrated experience applying data science to complex, commercially meaningful problems. You’ll combine technical depth with sound judgement, clearly connecting model and agent design decisions to customer outcomes, operational use and measurable business value.

Ideally, you will have:

  • Strong practical experience developing, evaluating and implementing machine learning or statistical models using large and complex datasets.
  • Experience with supervised learning, predictive modelling, classification, forecasting or related machine learning techniques.
  • Experience developing agentic AI, generative AI or large language model applications, including workflow design, evaluation methods and appropriate human oversight.
  • The ability to compare machine learning, rules-based and agentic approaches, then select an effective solution based on the problem, available data, risk and expected value.
  • Strong Python and SQL capability, with the ability to produce readable, testable and maintainable analytical or application code.
  • Experience defining evaluation measures that extend beyond model accuracy to include reliability, customer relevance, adoption and commercial outcomes.
  • An understanding of model validation, responsible AI, data governance, fairness and the safe use of customer data.
  • Strong communication and influencing skills, including the ability to explain complex technical concepts, challenge assumptions and recommend a clear course of action.

Working with us:

At CommBank, we're committed to creating an accessible, inclusive and respectful workplace. If you require support or adjustments, please let us know. We welcome applications from people of all backgrounds and we're particularly committed to making a positive difference for Aboriginal and/or Torres Strait Islander Peoples. For support please contact 1800 989 696.

If you're already part of the Commonwealth Bank Group (including Bankwest, x15ventures), you'll need to apply through Sidekick to submit a valid application. We’re keen to support you with the next step in your career.

We're aware of some accessibility issues on this site, particularly for screen reader users. We want to make finding your dream job as easy as possible, so if you require additional support please contact HR Direct on 1800 989 696.

Advertising End Date: 04/10/2026
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  • Role Data Scientist
  • Experience 3-4 years
  • Work type On-site
  • Location Australia
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CommBank
Financial Services & Fintech · 500+ Members · Australia

CommBank, the Commonwealth Bank of Australia, offers personal, business and institutional banking.

All jobs at CommBank
Job Overview
Eligibility
Australia Right to work in Australia required.
Workplace
On-site
Job Posted:
9 hours ago
Job Type
Full Time
Experience
3-4 years

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