Data Scientist

2x Fixed-term positions until 30 June 2027 available - can be based at any WorkSafe office location

We are open to inter-agency secondments, please speak to your manager before applying

About Us

Hello, Kia ora, Noa’ia, Talofa lava, Mauri, Mālō e lelei, Tālofa, Ni Sa Bula Vinaka, Fakaalofa lahi atu, Mālō ni, Kia orana , nǐ hǎo, Kamusta.

WorkSafe New Zealand | Mahi Haumaru Aotearoa is the primary workplace health and safety regulator. Our vision is that everyone who goes to mahi comes home healthy and safe. We live by our values:

• Whakakotahi – we are united in a strong purpose
• Kōrero mai – we engage meaningfully
• Tiakina mai – we are entrusted with a duty of care

About your team / Ko te tīma

Enterprise Planning and Implementation is a new group established at WorkSafe to strengthen planning, coordination, and implementation across the organisation, particularly to improve how work is prioritised, sequenced, and supported through to delivery.

The Data, Analytics and AI team is at the heart of enabling data-driven decision-making across WorkSafe and is responsible for building and maintaining the data assets to meet WorkSafe’s data, insights and intelligence needs. Working closely with analysts, architects, engineers, and business stakeholders, the team develops the data foundations that support reporting, analytics, and organisational performance.

About the role / Ō te tūranga

As a Data Scientist, you'll play a hands-on role in applying advanced analytics, machine learning and AI to complex regulatory and organisational problems. You'll work on things like risk-targeting projects that support prioritisation of regulatory activity, and AI agents that support frontline and regulatory work. Working alongside data engineers, analysts and business stakeholders, you'll design and deliver models and AI products that inform decision-making, improve our understanding of risk and harm, and support better outcomes for New Zealand workplaces.

What You'll Do/ Ko tōu ake mahi

• Design, build and validate advanced analytical models and AI solutions
• Apply statistical, machine learning and AI techniques to complex problems and datasets, including LLM-based approaches such as retrieval-augmented generation, agents and structured extraction.
• Design evaluation approaches for model and AI outputs, including test sets, human review and appropriate performance measures
• Support the transition of models and AI products into operational use, and monitor their performance once deployed
• Partner with data engineers, analysts and other specialists to deliver end-to-end solutions
• Translate analytical findings into practical insights, and clearly communicate what models can and cannot tell decision-makers

What You'll Bring / Ko ngā pukenga ōu

• Proven hands-on experience in delivering data science projects end-to-end, from problem definition and data preparation through to modelling, validation, deployment and monitoring in production.
• Strong Python (or R) and SQL skills, with experience using core data science and machine learning libraries
• Experience with or interest in LLM-based solutions such as RAG, agents or structured extraction, or machine learning
• Ability to explain technical concepts, evidence, limitations and uncertainty clearly to non-technical audiences
• A natural curiosity and a willingness to learn modern cloud and MLOps tools within our Azure ecosystem
• Relevant tertiary qualification in Data Science, Statistics, Mathematics, Computer Science or a related discipline, or equivalent practical experience

Nāu te rourou, nāku te rourou, ka ora ai te iwi.

Salary range / Awhe utu

As part of our remuneration framework, the full salary range is $103,059 -$135,004 per annum (KiwiSaver/SSRSS employer contributions are additional). From 1 April 2026 our KiwiSaver employer contribution increased to 3.5%.

We offer a range of benefits including:

• 5 weeks annual leave
• 15 days sick leave
• Flexible working arrangements
• A Reward and Recognition Framework that celebrates the impact our kaimahi make – your mahi matters
• Professional development opportunities
• Employee-led networks to promote the goals and needs of our diverse communities (Rainbow, Pacific, Women’s and Tū Rangatira Māori Network)

How to apply / Me pēhea te tono

WorkSafe has partnered with Randstad Digital for the recruitment of these vacancies. Please contact Amy Langhauser at amy.langhauser@randstaddigital.co.nz for a confidential discussion if you have any questions before applying.

Click Apply, and upload your CV and cover letter.

AI can be a helpful tool when preparing your application, but what matters most to us is you. Please ensure your CV, cover letter, and responses reflect your own skills, experiences, and perspective. We want to hear your real story - your passion, your personality, and what makes you unique. Don’t let AI do all the talking - let it support you, not replace you.

To be considered for this position, you must have the legal right to live and work in New Zealand.

Learn more about working with us: https://www.worksafe.govt.nz/about-us/careers/

This vacancy has been established as part of changes to WorkSafe's organisational structure after a review of WorkSafe's operating model identified opportunities to improve role clarity, ways of working and organisational effectiveness. As part of these changes, WorkSafe has established a number of new roles to ensure we are well placed to meet expectations now and in the future.

Kaimahi whose roles were affected by the structure change will be given preference for all vacancies and will be considered in the first instance.

Applications close: 11.59pm, 21st September 2026

Please note that we will be shortlisting and reviewing applications as we receive them. We encourage you to apply early as we may withdraw advertising prior to the closing date above if preferred applicants are identified sooner.

At Randstad, we are passionate about providing equal employment opportunities and embracing diversity to the benefit of all. We actively encourage applications from any background.