Workforce Modeller

About us | Mō mātou

ACC is a trusted and high-performing organisation, providing care, supporting recovery and promoting injury prevention, now and into the future.

You can find more about ACC and the work we do here.

About the role | Mō te tūranga mahi

As a Workforce Modeller, you will play a key role in shaping how our Service Delivery workforce is planned and supported. This role focuses on developing, maintaining, and continuously improving complex models that guide operational decision-making. Your modelling insights will help ensure we have the right workforce capacity, at the right time, to meet customer needs and achieve our strategic goals.

This is a permanent full-time opportunity, within the Workforce Management team, flexible location options include Auckland, Hamilton, Wellington, Christchurch, or Dunedin.

In this role, you will:

• Deliver accurate modelling, forecasts, prototypes, and analytical solutions that enable effective business decisions

• Extract, transform, and analyse complex datasets using tools such as Python, SQL, SAS or R to generate actionable insights

• Document modelling methodologies to ensure transparency and reproducibility

• Provide expert advice on how operational or process changes may affect workforce capacity and performance

• Prepare clear summaries, visualisations, and presentations to communicate analytical findings to diverse stakeholders

• Identify improvements to existing models, reporting processes, and analytical tools to enhance accuracy and efficiency

• Contribute to validation, testing, peer review, and continuous uplift of modelling capability across the team

About you | Mōu

You have strong technical capability and a passion for translating complex data into meaningful insights. Working well independently while thriving in a collaborative team environment, you apply best‑practice methodologies and contribute to building capability by upskilling colleagues. Experience with workforce management or planning concepts is beneficial but not essential. Your expertise with models and analytics is what matters most.

You will bring:

• Demonstrated experience building and implementing analytical or statistical models (Excel, SAS, R, Python, SQL)

• Strong data literacy and ability to analyse complex data sets

• Experience with data visualisation tools such as Power BI or Tableau

• Excellent written and verbal communication skills

• Ability to understand business needs and translate them into model requirements and insights

• Strong critical thinking, problem‑solving, and prioritisation skills

• Ability to work in a structured project or delivery environment

• Understanding of performance reporting, modelling frameworks, and analytical methodologies

• Cultural capability, including demonstrated application of Te Tiriti o Waitangi principles in your work

Working at ACC | Mō ACC

At ACC, we embrace the rich tapestry of Aotearoa New Zealand’s cultures and are dedicated to providing equitable opportunities. We know that a diverse and inclusive team helps us meet the needs of our customers, and we encourage applications from individuals of all backgrounds, ethnicity, national origin, gender identity, age, and those with diverse abilities. It is important to us that people are free to be themselves at work.

The appointing salary for this role will sit between $101,287 and $119,161 and we offer an additional 9% superannuation contribution. ACC offer a comprehensive benefits package, including an advantageous superannuation scheme with features like 0% contribution required by you, optional life and income protection insurance, and the flexibility to change to a locked plan at any time, ensuring your financial security now and in retirement.

How to apply | Me pēhea te tuku tono

As part of your application, please provide answer to the following question with your CV/ Cover Letter:

• Please provide an example of piece of modelling that you have completed and the benefit that was delivered.

• Please indicate your desired hub location

Applications close 5pm, Sunday 31 May 2026 however, please note that if an ideal candidate is found during this time we will move forward with screening and interviewing sooner. If you experience any accessibility issues or have pātai (questions), please contact [email protected].