Senior Data Scientist

Randstad

Auckland

On-site

NZD 121,000 - 158,000

Full time

9 days ago

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Benefits offered by this job

5 weeks annual leave

15 days sick leave

Flexible working arrangements

Reward and Recognition Framework

Professional development opportunities

Employee‑led networks (Rainbow,Pacific

Job summary

WorkSafe New Zealand is seeking a Senior Data Scientist to apply advanced analytics, ML and AI to regulatory and organisational challenges. You’ll design and deploy models and AI products that inform decision-making and help improve workplace safety across New Zealand.

You’ll work with data engineers, analysts and stakeholders, mentor others, and help lift technical practice within the team, including RAG, agents and structured extraction techniques in production.

Qualifications

Substantial hands-on experience 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 LLM-based solutions such as RAG, agents or structured extraction, or strong classical ML depth and a demonstrated interest in developing this capability.
Sound judgement in model validation, including selecting appropriate performance measures and identifying risks such as data leakage, overfitting and class imbalance
Experience working in a cloud environment (Azure preferred) and familiarity with MLOps practices
Strong capability working with large, complex or incomplete datasets
Ability to explain technical concepts, evidence, limitations and uncertainty clearly to non-technical audiences
Experience mentoring others or lifting technical practice within a team
Relevant tertiary qualification in Data Science, Statistics, Mathematics, Computer Science or a related discipline, or equivalent practical experience

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
Set and lift technical practice across the team, including code review, reproducibility, documentation and MLOps
Mentor and support less experienced data scientists
Translate analytical findings into practical insights, and clearly communicate what models can and cannot tell decision-makers

Skills

Python

SQL

LLM-based solutions

Machine learning

Data modeling

MLOps

Mentoring

Communication to non-technical

Education

Bachelor Degree in Data Science, Statistics, Mathematics, Computer Science or related discipline

Tools

Azure Cloud

LLM tooling

Job description

Permanent, full-time position - can be based at any WorkSafe office location

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 Senior Data Scientist, you'll apply 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
Set and lift technical practice across the team, including code review, reproducibility, documentation and MLOps
Mentor and support less experienced data scientists
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

Substantial hands‑on experience 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 LLM‑based solutions such as RAG, agents or structured extraction, or strong classical ML depth and a demonstrated interest in developing this capability.
Sound judgement in model validation, including selecting appropriate performance measures and identifying risks such as data leakage, overfitting and class imbalance
Experience working in a cloud environment (Azure preferred) and familiarity with MLOps practices
Strong capability working with large, complex or incomplete datasets
Ability to explain technical concepts, evidence, limitations and uncertainty clearly to non‑technical audiences
Experience mentoring others or lifting technical practice within a team
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 for this position is $120,551-$158,328 with the expected appointment base salary $120,551 - $133,143 (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)

Applications close: 11.59pm, 14th September 2026

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.

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.

skills

Data Science

qualifications