Australian Institute of Health and Welfare
APS6 Senior Data Analysts (Bulk Round)
Skills
2 months ago
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Important information
Contract type:
Permanent
Location:
Sydney NSW, Australia
Work mode:
Hybrid
Published on:
3 September 2026
What they need
The AIHW is seeking experienced and enthusiastic Senior Data Analysts to join our high-performing and collaborative units across the institute. The successful candidates will possess a high level of technical knowledge in statistical and research project work including the ability to work with complex and sensitive information.
Our Senior Data Analysts support our business areas to deliver our analytical, data improvement and project work.
Vacancies currently exist across the following work areas:
- Defence and Veterans Insights
- Chronic Conditions
- The Burden Health Economics of Disease and Mortality
- Health Economics
- Hospitals Data
- Housing and Homelessness Reporting and Development
- Injury Data
- Sexual and Reproductive Health
- Cancer Data Development
- Screening Analysis & Monitoring
- Ethics and Privacy
- Aged Care
- Dementia
- Perinatal
Senior Data Analysts will perform the following functions:
- Working with data and large databases, including data validation and processing.
- Undertaking complex research and statistical analysis and interpretation of data.
- Designing, researching, analysing, and presenting information in various formats.
- Data linkage and integration.
Under general direction, these roles may include:
- planning, organising, and managing projects.
- manipulating and interrogating databases using software such as SAS, R, Python, SQL or other software.
- liaising and negotiating with internal and external stakeholders, including government agencies, state and local authorities, and business or community organisations.
- leading a small team, including managing team priorities and deliverables.
- drafting of committee papers.
We are increasingly making use of emerging technologies used in evaluation and data science with advanced analytics techniques such as AI, predictive and scenario modelling, machine learning, and data mining.
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