- Build data products and join Qantas’ AI journey from the beginning
- Permanent opportunity based at our Mascot office (hybrid working with 3 days in the office baseline)
- Staff Travel Benefits from Day One
As a Senior Data Scientist, you’ll play a pivotal role in shaping how data science and AI come to life at Qantas. As part of our data modernisation, we’re building a modern data platform, data products to support our AI ambitions, and AI infrastructure to operate at scale.
This is an opportunity to lead the design, delivery and ongoing operation of high-impact AI/ML and data products, and their use in Qantas’ AI ambitions. You’ll bring together systems, data, processes and people to unlock stronger customer and commercial outcomes, while maintaining a clear focus on data security, governance and compliance.
Key Responsibilities:
- Help shape our data transformation from the outset, identifying business needs, defining and building data products to support our ambition to bring AI to life at scale across the airline
- Build deep expertise in how our data reflects the way the business operates, and use it to guide the business on its AI journey.
- You’ll deliver end-to-end, scalable and innovative AI/ML solutions, including productionisation, automation, and implementation of AI models for the respective business domain
- You’ll actively contribute to improving ML Ops practices and standards.
- You’ll champion AI solutions and contribute to the Data Science community.
- Given a business problem to solve, you’ll help uncover insights from diverse data sources and turn them into practical recommendations that support strategic decision-making.
- You’ll lead the scoping and delivery of key analytics projects, developing a deeper understanding of customer behaviour, operational drivers, how we forecast and budget, and the critical inputs that influence business performance.
- You’ll provide expert technical advice and direction to project teams on complex research and insight initiatives.
- You’ll partner closely with Technology & Platform teams, Product, Support, Change, Commercial Process Integration, Data Science and Engineering teams to translate business challenges into fit-for-purpose analytical solutions.
- You’ll influence strategic decision-making by providing clear, practical recommendations, robust modelling outputs and stakeholder-friendly insights.
You’ll have:
- Tertiary qualifications in applied statistics, mathematics, computer science, data science, econometrics, engineering or a related quantitative field; post-graduate qualifications are advantageous.
- 5+ years’ experience in a data science, analytics, AI, developer or similar role, ideally within aviation, retail, telco, finance or a commercial analytics environment.
- Hands-on ML/AI experience is essential.
- Practical experience with modern data science tooling e.g. Python, Docker, SQL, Git and CI/CD systems, dbt, Airflow etc
- Experience with data visualisation tools e.g. Streamlit, Power BI and bespoke dashboarding tools.
- Experience using AI-assisted coding to accelerate development, with appropriate guardrails and review to ensure the output is correct
- Confident using statistical techniques such as regression analysis, hypothesis testing, cluster analysis and time series analysis on large datasets.
- Ability to solve complex business problems and translate business challenges into analytical requirements.
- Strong stakeholder engagement, communication, influencing and presentation skills, with the ability to explain complex insights and recommendations to senior leaders.
- A positive, pragmatic and resilient mindset, with the ability to work collaboratively, champion new ways of working
- Experience building data models on a modern cloud data platform, including data cataloguing, lineage and metadata management tooling.
Why Qantas?
You’ll join a team where creativity and passion are encouraged. Our people come together to allow us to dream big and deliver successfully.
There are many different opportunities across our team, which means you’ll be able to grow both personally and professionally at Qantas. Your development is a priority for us – so that you can maintain the high standards our customers have come to expect and can continue to develop over time. You’ll be supported from day 1 with on the job training and coaching as well as our formal training opportunities. While you may start in this role, we’ve got a great track record of supporting our people to take their career in so many different directions, the destinations are endless.
The Qantas employee benefits program offers amazing benefits that extend well beyond travel:
- We love to travel: Enjoy heavily discounted air travel within Australia and across the globe, both for you and your family and friends, as well as exclusive deals on accommodation and holidays.
- We have flexible leave options: Make use of leave and flexible working opportunities including 18 weeks paid parental leave (plus superannuation payments on all paid and unpaid parental leave until your child turns 1) and additional purchased leave options for eligible employees.
- We’ll give you access to thousands of rewards: Through our partnerships we can offer you discounts across shopping, food and wine, insurance, health and wellbeing, leisure and entertainment. You can also take advantage of our salary packaging program including motor vehicles, eligible portable electronic devices and professional memberships.
- We’ll support your wellbeing: Whether it’s learning to better support your own and others’ mental health, our interactive wellbeing app or your very own tailored nutrition plan.
Qantas is an Equal Opportunity Employer, so by coming to work for us, you’ll be part of an organisation that encourages diversity, supports charities and environmental initiatives. We encourage Aboriginal and Torres Strait Islander – and people from every other kind of background – to apply. We are committed to creating an inclusive workplace. Talk to us about how this job could be flexible for you.
Applications will close by the 8th of October