AI Science Lead - Customer Initiatives
Westpac Group · Sydney
- Sydney, Melbourne, or Brisbane Based
- Hybrid Working
How will I help?
Customer data is full of signals. The opportunity is turning those signals into decisions and interventions that are useful, fair and measurable. Westpac is looking for a Lead AI Scientist to own our whole-of-customer intelligence strategy and technical roadmap and lead the team bringing it to life.
Reporting to the Head of AI, you will partner across Consumer product lines, channel owners and Data, Digital and AI (DDAI) teams as their trusted technical adviser on customer intelligence. You will stay close to the science, from data design and feature engineering through predictive and causal modelling, experimentation, deployment and monitoring, while creating the clarity and support your team needs to deliver its best work.
This is a hands-on role with real influence: you will see the whole customer journey, find the signals that matter and shift the outcome.
Your mission: build shared customer intelligence that product lines adopt, trust and reuse, connecting customer signals to better experiences, deeper engagement, smarter retention and more effective support.
What will I be responsible for?
- Own the whole-of-customer intelligence roadmap with product line partners, aligned to divisional and enterprise AI strategies and agreed priorities.
- Partner with business owners to frame and prioritise use cases with clear decisions, interventions, success measures and accountable owners.
- Lead the team's technical direction across data design, feature engineering, predictive and causal modelling, and experimentation.
- Create shared customer definitions, features and measurement approaches so models give consistent signals across products and channels.
- Be accountable for the quality of the team's solutions across problem definition, validation, deployment, monitoring and retirement.
- Ensure every solution meets Group AI risk policies, embedding privacy, security, model risk, Responsible AI, explainability, fairness, human oversight and operational resilience.
- Agree interfaces, acceptance criteria and owners for embedding models into customer treatments.
- Monitor adoption, model performance, realised value and customer-harm indicators, intervening or escalating when outcomes or controls are at risk.
- Lead, coach and grow an inclusive, high-performing team, and build reusable customer features and models that product lines adopt rather than rebuild.
What do I need?
- 8+ years in data science and applied AI, including senior leadership, with recent hands-on practice in complex, highly regulated financial services environments.
- Deep expertise in customer analytics and decision intelligence, feature engineering, predictive modelling, causal inference and experimentation.
- Production experience building customer value, retention, engagement or next-best-action solutions, beyond strategy or proof-of-concept work.
- A thorough grasp of vulnerability, fairness, privacy, model risk, explainability, human oversight and customer-harm safeguards.
- Experience managing the model lifecycle from feature design through deployment, monitoring and retirement.
- Proven people leadership with line-management accountability, including coaching technical leaders, building team capability, setting direction and managing performance.
- Executive influence and cross-functional delivery skills, with the ability to turn complex technical evidence into clear, practical decisions.
- Applied experience with complaints, customer feedback, NLP or GenAI, and the judgement to use these tools responsibly.
- Experience contributing reusable models, features or evaluation approaches across a wider practice or community.
Why does this role stand out?
- Own the whole-of-customer intelligence strategy and technical roadmap in a newly created role.
- Shape customer decisions across experience, value, retention and support.
- Lead deep technical work across feature engineering, predictive and causal modelling, experimentation, NLP and GenAI.
- Create measurable customer and commercial outcomes without losing sight of fairness, vulnerability or customer harm.
- Lead and grow an inclusive team of AI professionals and technical leaders, and contribute reusable features, models and lessons across the wider AI Science practice.
Does this sound like you?
To get started, simply click on the APPLY or APPLY NOW button. Please note that application closing dates are subject to change so don’t delay putting your best foot forward!
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