Lead Data Scientist

Hybrid Full TimeSydney, New South Wales, AustraliaWestpac Group

Join Westpac’s centralised DDAI team and help shape how Generative AI and advanced ML create real customer and colleague impact across the bank. You’ll build and deploy production-grade solutions end-to-end, influence best practice, and help grow a Data Science Centre of Excellence—setting the standard for responsible, scalable AI.

Requirements

  • Significant experience delivering and deploying both ML and GenAI solutions with measurable outcomes.
  • Strong hands-on capability in deep learning / generative models (reinforcement learning experience desirable).
  • Solid experience with ML and Agentic frameworks such as TensorFlow, PyTorch, Keras, AutoGen, LangChain or LlamaIndex etc. and strong Python engineering
  • Expertise in one or more of: NLP / LLMs / GenAI, or Computer Vision; plus, tools such as Microsoft AI Services (e.g., audio-to-text, text mining, image recognition) and/or OpenAI capabilities.
  • Experience working with Azure platforms preferable.
  • Strong stakeholder engagement: you can translate business needs into robust, responsible solutions.
  • Demonstrated leadership—mentoring, guiding delivery, and lifting team practice.

Benefits

  • Flexible work arrangements
  • Various leave options including Culture, Lifestyle and Wellbeing leave
  • Exclusive offers on banking products
  • Discounts from top brands
  • Generous employee-only mortgage rates
  • Tailored learning and development opportunities
  • Opportunities to ‘give back’ to the Community

Before applying for this position you need to submit your online resume. Click the button below to continue.

Tired of manual job applications?

JobCopilot auto-applies to thousands of RevOps and GTM roles on your behalf — so you can focus on interviews, not applications.

Applying for this role?

Tailor your resume to this exact role — hiring managers notice the difference.

Latest articles on the blog

RECRUITERS!

Reduce the risk of your recruitment process (applicant quality, long and inefficient process) by selecting from a relevant pool of candidates.

POST A NEW JOB NOW!