Chapter Lead - AI - Home Buying (Lead Data Scientist)

CommBank; Sydney; On-site; AUD 180,000 - 260,000; Full time

Job summary

CommBank seeks a Chapter Lead - AI for Home Buying to guide a team of Data Scientists, delivering world‑class AI capabilities across Retail Banking Services. You will drive GenAI and agentic AI initiatives, architecting solutions that delight customers and advance the bank’s AI strategy.

You will report to the Home Buying Chapter Area Lead, delivering high‑priority AI projects, and collaborating with stakeholders to elevate data science practices and outcomes across the organisation.

Qualifications

• Experience leading Data Science teams and delivering AI solutions in large organisations.
• Strong track record in GenAI and agentic AI initiatives with measurable impact.
• Hands-on expertise with Spark, Python, R, TensorFlow, PyTorch and SQL in production environments.
• Familiarity with cloud platforms (AWS/Azure) and deployment pipelines.

Responsibilities

• Lead GenAI and agentic AI system design and development across RBS.
• Oversee ML model development and deployment to drive business outcomes.
• Identify AI opportunities and embed methodologies across the banking landscape.
• Collaborate with stakeholders to evangelise and scale AI capabilities.

Skills

Technical Leadership

GenAI

Machine Learning

Data Engineering

Cloud Architecture

CI/CD

Version Control

Spark

Python

R

TensorFlow

PyTorch

SQL

Tools

Spark

Python

R

TensorFlow

PyTorch

SQL

Docker

Job description

Chapter Lead - AI - Home Buying (Lead Data Scientist)

We look forward to welcoming a technical leader who will drive impactful projects, lead and mentor a team of Data Scientists, harness cutting‑edge AI technologies and pioneer innovative practices that benefit not only CommBank but the banking industry as a whole.

See yourself in our team:

At CBA we have an ambitious goal of leading the way in changing the world through AI. With great buy‑in from all senior leadership, we have embarked on world first initiatives to deliver exceptional experiences to our customers. In Retail Banking Services (RBS), as the largest and customer facing part of the bank, we play a unique role in bringing this vision to life and build a brighter future for all Australians.

The opportunity:

Reporting to the Home Buying Chapter Area Lead, you will deliver high priority initiatives across RBS. You will lead the delivery of world‑class AI capabilities across RBS that will also build capabilities for the rest of CBA. You will be responsible for cutting edge initiatives in agentic AI, GenAI, and broader AI. Our strategic focus lies in delighting our customers at every touchpoint, offering outstanding service, and meet the needs of our customers.

Why CommBank?

CommBank is leading the world of banking by venturing into new‑to‑the‑world innovations. We're on the cutting edge, embracing AI technologies to reshape how we operate and serve our customers. When you join CommBank, you’re joining a team that values expertise and innovation, and you’ll be empowered to lead projects that push the boundaries of what's possible.

Key Responsibilities:

• Lead GenAI and Agentic system design and development: Drive the expansion and adoption of Generative AI solutions across RBS, optimising our product offerings through design and implementation of advanced Gen AI capabilities and agentic AI systems.
• Develop and implement Machine Learning Models: Lead the overhaul of various machine learning models, enabling to drive strategic business outcome for various stakeholders.
• Expand Data/AI Science Usage: Identify AI opportunities and embed these methodologies into a broader range of activities across the banking landscape
• Drive Continuous Improvement and Business Outcomes: work closely with business stakeholder to pioneer adoption and application of cutting edge AI and Gen AI capabilities and paving the path for how the bank will operate to towards the vision of re-imagined banking and customer service.

We’re interested in hearing from people with the following skills.

• Technical Leadership and Coordination:
  • Ability to coordinate effectively across the Data Science community to unify efforts and drive collaborative outcomes.
  • Demonstrated capability in driving outcomes that are reusable and can be leveraged across the group.
  • Intellectual curiosity and ability and willingness to learn, experiment and lead new to the world concepts
• Technical Skills and Tools:
  • Machine Learning: Expertise in the design and construction of machine learning models, including feature engineering, model selection, hyperparameter tuning, model evaluation, and deployment of predictive models into production environments.
  • Generative AI: Familiarity with various aspects of Generative AI, including prompt engineering, Retrieval‑Augmented Generation (RAG), guardrail design, orchestration design, and tools such as LangChain and LangGraph.
  • Cutting-Edge AI: Work on projects leveraging traditional AI, Generative AI, and agentic AI to pave the path for how banking and broader industry functions in the future.
  • Version Control and CI/CD: Experience with version control and CI/CD pipelines such as GitHub.
  • Tooling: Hands‑on experience with data science tools such as Spark, Python, R, TensorFlow, PyTorch, and SQL.
  • Data Engineering: Knowledge of ETL processes and data pipeline construction, ensuring efficient data flow and integration.
  • Deployment: Familiar with Docker for containerization and deployment of applications.
  • Cloud Architecture: Grounded understanding in AWS or Azure Cloud architecture and integration, demonstrating experience in deploying and managing cloud‑based solutions.

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