Senior Data Scientist: Lead AI & Data Products (Hybrid)

Qantas Airways; Sydney; Hybrid; AUD 150,000 - 210,000; Full time

Benefits offered by this job

Staff Travel Benefits from Day One

Job summary

Qantas Airways is seeking a Senior Data Scientist to lead AI/ML data products as part of our data modernisation. You will shape data platforms, drive end-to-end AI solutions and ensure governance and security across the stack.

The role requires 5+ years in data science or related fields, hands-on ML/AI, and strong skills in Python, SQL, Docker, Git, and CI/CD, with experience in data visualization tools and cloud data platforms. Hybrid work from Mascot with staff travel benefits from day one.

Qualifications

• Tertiary qualification in applied statistics, mathematics, computer science, data science, econometrics, or engineering.
• Post-graduate qualifications are advantageous for this senior role.

Responsibilities

• Shape data transformation from the outset to support AI at scale across the airline.
• Build data understanding to guide the business on its AI journey.
• Deliver end-to-end, scalable AI/ML solutions including productionisation and automation.
• Improve ML Ops practices and standards.
• Champion AI solutions and contribute to the Data Science community.
• Translate business challenges into analytical requirements for stakeholders.
• Lead analytics projects to understand customer behaviour, operational drivers and forecasting inputs.
• Provide expert technical direction to project teams on research and insights.

Skills

ML/AI experience

Python

Docker

SQL

Git

CI/CD

dbt

Airflow

Streamlit

Power BI

Statistical analysis

Stakeholder management

Education

Statistics/Math/CS degree

Post-graduate qualifications advantageous

Tools

dbt

Airflow

Power BI

Streamlit

Job description

Qantas Airways is seeking a Senior Data Scientist to lead AI/ML data products as part of our data modernisation. You will shape data platforms, drive end-to-end AI solutions and ensure governance and security across the stack.

The role requires 5+ years in data science or related fields, hands-on ML/AI, and strong skills in Python, SQL, Docker, Git, and CI/CD, with experience in data visualization tools and cloud data platforms. Hybrid work from Mascot with staff travel benefits from day one.