Kia ora!
At Air New Zealand, data drives the way we understand our customers, plan for the future, and make strategic commercial decisions. We’re looking for an experienced Data Science Chapter Lead with deep expertise in forecasting, predictive modelling, and customer analytics to lead our next wave of innovation.
About the Role
This is a key leadership position for someone who thrives at the intersection of data science and business impact. You'll lead a high-performing chapter of data scientists focused on solving complex customer and commercial problems — from building market demand forecasts to optimising pricing models and enhancing customer engagement strategies.
You’ll be responsible for setting the vision and standards for how advanced analytics is applied across our customer and commercial domains, ensuring that the models your chapter delivers are scalable, explainable, and deliver measurable value.
What You’ll Be Doing
- Leading the development of advanced forecasting models to inform network, revenue, and demand planning.
- Shaping and executing customer analytics strategies, including segmentation, lifetime value, churn prediction, and propensity modelling.
- Partnering with commercial, marketing, and customer teams to embed predictive insights into campaigns, product design, and pricing strategies.
- Establishing best practices for model governance, experimentation, and production deployment.
- Building technical capability across your chapter by mentoring and supporting career development of data scientists.
- Helping the organisation make smarter, faster decisions by championing the role of data in commercial and customer domains.
What You’ll Bring
- Proven experience leading data science teams with a strong focus on customer, marketing, or commercial analytics.
- Deep knowledge of forecasting, time series analysis, predictive modelling, and causal inference.
- Demonstrated success delivering scalable models in production environments that influence business decisions.
- Strong communication and stakeholder engagement skills — you can influence senior leaders with evidence and insight.
- Hands-on experience with modern data science tools and languages (e.g., Python, SQL, Spark) and cloud platforms (e.g., AWS, GCP).
- Passion for growing people, building communities of practice, and fostering technical excellence.
Why Join Us
You’ll have the opportunity to shape how analytics drives one of New Zealand’s most loved and globally recognised brands. This role offers a rare chance to apply world-class data science techniques in a business with rich, complex customer and commercial challenges — and to do so in a supportive, forward-thinking environment that values innovation and impact.
We offer competitive compensation, flexible working, and the chance to work on projects that are both analytically interesting and business critical.
If you're passionate about using data to shape smarter commercial decisions and deeper customer understanding, we’d love to hear from you.
Applications close 13th July 2025.
Additional Information
At Air New Zealand, we are proudly committed to diversity, equity and inclusion and believe in creating a truly inclusive workplace where everyone can be themselves and thrive. Our people are our greatest asset – because while everything else we do in our operation can be replicated by our competitors, it is our people that truly set us apart. We are firm believers in celebrating the differences and diversity of thought our people bring to their roles. We encourage candidates from diverse backgrounds, including those with a disability, additional health and mental health needs, and/or are neurodiverse to apply for our roles.
If you have encountered any accessibility barriers and require further information or reasonable accommodations to our recruitment process, please reach out to the recruiter listed on this job advert so they are able to support you to freely participate equitably in our recruitment and selection process.
Whāia te pae tawhiti kia tata. Ko te pae tata whakamaua, kia tina.
"Seek to bring distant horizons closer. Once near, seize them and make them your reality."
