YOUR SKILLS AND EXPERIENCE/KĀ PŪKEKA ME KĀ WHEAKO

To be successful in this role you will ideally have:

• A completed or in‑progress Master’s qualification in a relevant area.
• Experience in machine learning, artificial intelligence, or statistical modelling, with knowledge of tree‑based ensemble methods desirable.
• Proficiency in R, Python, and/or other statistical software for AI statistical methods and modelling.
• A track record of contributing to scientific publications.
• Discretion and proven ability to manage highly sensitive or confidential information.
• Highly developed interpersonal, written, and verbal communication skills.
• Experience with the Integrated Data Infrastructure (IDI) and geospatial data analysis (beneficial but not essential).

THE ROLE/TE MAHI

We are seeking a motivated Statistician to join the Better Ageing with Big Data Group within the Department of Medicine.
In this position, you will contribute to the Leveraging AI for Health Ageing programme, recently awarded inaugural funding through the New Zealand–Singapore Artificial Intelligence Research Grant, by providing advanced statistical and AI analysis, and supporting all aspects of the project, including ethics, publication, dissemination, and project management.

Key responsibilities include:

• Performing statistical and AI analysis and reporting findings.
• Creating cross‑walks between New Zealand and international data.
• Training models with national and international datasets.
• Supporting applications for ethical approval.
• Contributing to scientific papers and future grant applications.
• Preparing regular progress reports.
• Spending up to four months travelling nationally or potentially internationally.
• Building strong working relationships within the University and with key stakeholders.
• This is an exciting opportunity to contribute to research that supports better ageing outcomes through the use of big data and innovative analysis.

To be successful in this role you will ideally have:

• A completed or in‑progress Master’s qualification in a relevant area.
• Experience in machine learning, artificial intelligence, or statistical modelling, with knowledge of tree‑based ensemble methods desirable.
• Proficiency in R, Python, and/or other statistical software for AI statistical methods and modelling.
• A track record of contributing to scientific publications.
• Discretion and proven ability to manage highly sensitive or confidential information.
• Highly developed interpersonal, written, and verbal communication skills.
• Experience with the Integrated Data Infrastructure (IDI) and geospatial data analysis (beneficial but not essential)