AI Science Lead - Customer Initiatives

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

Job summary

Westpac in Australia seeks a Lead AI Scientist to own the 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 and 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 clarity and support

Qualifications

• 8+ years in data science and applied AI, including senior leadership.
• 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.
• Experience managing the model lifecycle from feature design through deployment, monitoring and retirement.
• Proven people leadership with line-management accountability.
• Executive influence and cross-functional delivery skills.
• Applied experience with complaints, customer feedback, NLP or GenAI.

Responsibilities

• Own the whole-of-customer intelligence roadmap with product line partners.
• Partner with business owners to frame and prioritise use cases with clear decisions and success measures.
• Lead the team's technical direction across data design, feature engineering, modelling, and experimentation.
• Create shared customer definitions and measurement approaches for consistent signals.
• Ensure solutions meet AI risk policies including privacy, security, and explainability.
• Monitor adoption, model performance and customer-harm indicators.
• Grow an inclusive, high-performing team and build reusable features and models.

Skills

Data science

Applied AI

Senior leadership

Customer analytics

Decision intelligence

Feature engineering

Predictive modelling

Causal inference

Experimentation

NLP/GenAI

Model lifecycle

People leadership

Executive influence

Cross-functional delivery

Risk & ethics

Job description

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?

We’re all about creating a supportive and inclusive community. We welcome everyone – no matter your age, gender, background, or abilities. We also provide added support to welcome our veterans, Indigenous Australians, and neurodiverse community.

If you need any adjustments during the recruitment process, you can find out more information and additional contact details by visiting the "People with Disability and/or needing Accessibility Requirements" page on our website .