Data Scientist — GenAI & Customer Experience

Commonwealth Bank; Sydney; On-site; AUD 150,000 - 210,000; Full time

Job summary

Commonwealth Bank is seeking a Data Scientist to join a Growth squad focused on data, ML and AI to enhance home lending customer experiences. You will work on complex datasets to develop predictive models and intelligent apps that turn data into practical insights.

You will own the data science lifecycle from framing problems to deployment and monitoring, balancing technical performance with responsible data use and commercial value. Strong Python/SQL and ML foundations are essential.

Qualifications

• Strong foundations in statistics, mathematics and machine learning.
• Experience applying data science to complex, commercially meaningful problems.
• Proficient Python and SQL with readable, maintainable code.
• Experience developing agentic or generative AI solutions.
• Ability to design evaluation measures beyond accuracy and to drive business value.
• Understanding of responsible AI, data governance and model validation.
• Excellent communication to explain complex concepts and recommend actions.

Responsibilities

• Identify and optimise customer cohorts for home lending opportunities using analytics and predictive modelling.
• Design, run, and measure experiments to evaluate propositions and improve outcomes.
• Develop AI-powered solutions, including GenAI, to enhance customer conversations and personalisation.
• Decide on the best approach (ML, rules, agentic) for problems and opportunities.
• Build robust experimentation and evaluation frameworks balancing performance, reliability and business value.

Skills

Stats & ML foundations

Data science in business

Python & SQL

Agentic/GenAI experience

Experimentation & evaluation

Responsible AI & data governance

Communication & influence

Tools

Python

SQL

GenAI

LLM apps

Job description

Commonwealth Bank is seeking a Data Scientist to join a Growth squad focused on data, ML and AI to enhance home lending customer experiences. You will work on complex datasets to develop predictive models and intelligent apps that turn data into practical insights.

You will own the data science lifecycle from framing problems to deployment and monitoring, balancing technical performance with responsible data use and commercial value. Strong Python/SQL and ML foundations are essential.