data scientist

Randstad Digital New Zealand

Christchurch

On-site

NZD 103,000 - 135,000

Full time

2 days ago

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Benefits offered by this job

5 weeks annual leave

15 days sick leave

Flexible working

Reward & Recognition Framework

Professional development opportunities

Employee networks (Rainbow, Pacific,女性

Job summary

WorkSafe New Zealand is seeking a Data Scientist to apply advanced analytics, machine learning and AI to regulatory and organisational challenges. You’ll build models and AI products that inform decision‑making and support safer workplaces across Aotearoa.

Collaborating with data engineers and analysts, you’ll design end‑to‑end solutions, validate results, and translate insights for non‑technical stakeholders.

Qualifications

Proven end-to-end data science project delivery.
Strong Python (or R) and SQL skills.
Experience with or interest in LLM-based solutions like RAG or agents.

Responsibilities

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

Skills

Python

SQL

LLM-based solutions

Communication

Azure cloud

MLOps

Education

Bachelor's degree in Data Science/Statistics/Math/CS

Tools

Pandas

Scikit-learn

Azure ML

Job description

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

He aha te mea nui o tēnei ao? He tangata, he tangata, he tangata. ...

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)

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

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

We actively encourage applications from any background.

Data Science