Data Scientist

Commonwealth Bank; Sydney; On-site; AUD 120,000 - 180,000; Full time

Job summary

Commonwealth Bank is seeking a Data Scientist to build machine learning and agentic AI solutions that deepen customer understanding and improve conversations across the home lending journey.

You will lead projects from framing problems to deployment and monitoring, balancing performance with responsible data use and business impact.

Qualifications

• Strong foundations in statistics, mathematics and machine learning.
• Experience applying data science to complex, commercially meaningful problems.
• Strong Python and SQL capability, with readable, maintainable code.

Responsibilities

• Identify and optimise customer cohorts for home lending opportunities using analytics and predictive modelling.
• Design, execute and measure experiments to evaluate customer propositions and actions.
• Develop and apply AI-powered solutions, including GenAI and agentic capabilities, to enhance customer communications and personalise experiences.

Skills

Statistics

Mathematics

Machine learning

Experimentation design

Communication

Education

Degree in Statistics/Mathematics/Data Science

Tools

Python

SQL

GenAI

Agentic AI

Large Language Models

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

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:

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Advertising End Date: 16/10/2026