Data Scientist

About WorkSafe New Zealand

WorkSafe New Zealand is the main regulator for workplace health and safety, with a mission that everyone returns home healthy and safe after work. The organization values unity of purpose, meaningful engagement, and a strong duty of care.

The Team

The Enterprise Planning and Implementation group is newly formed to improve planning, coordination, and delivery across WorkSafe. Within this group, the Data, Analytics and AI team supports data-driven decision-making by creating and maintaining critical data assets, collaborating closely with analysts, architects, engineers, and stakeholders to facilitate reporting, analytics, and performance measurement.

Role Overview

The Data Scientist will actively apply advanced analytics, machine learning, and AI techniques to address complex regulatory and organizational challenges. Key projects include risk-targeting to prioritize regulatory activities and developing AI agents that aid frontline and regulatory teams. Collaborating with data engineers, analysts, and business teams, you will design, develop, and implement AI models and products that enhance risk understanding and improve workplace outcomes across New Zealand.

Key Responsibilities

• Create, construct, and validate sophisticated analytical models and AI applications.
• Utilize statistical, machine learning, and AI methods on multifaceted datasets, including LLM-based technologies such as retrieval-augmented generation, AI agents, and structured information extraction.
• Devise evaluation frameworks for model outputs incorporating test datasets, human assessment, and relevant performance metrics.
• Facilitate the deployment and operational integration of models and AI solutions, monitoring their performance post-launch.
• Collaborate closely with data engineers, analysts, and specialists to deliver comprehensive end-to-end solutions.
• Translate complex analytical results clearly and effectively to non-technical decision-makers, outlining the capabilities and limits of the models.

Candidate Qualifications and Skills

• Demonstrated experience managing data science projects through all phases — from problem definition and data preparation to modelling, validation, deployment and ongoing monitoring.
• Proficiency in Python or R and SQL, with familiarity in key data science and machine learning libraries.
• Experience or keen interest in working with LLM-based approaches such as retrieval augmented generation, AI agents, or structured extraction methods.
• Strong communication skills for explaining complex technical concepts, evidential findings, and any uncertainties to audiences without technical background.
• A curious mindset with eagerness to learn new cloud technologies and MLOps within the Azure platform.
• A relevant tertiary qualification such as a degree in Data Science, Statistics, Mathematics, Computer Science or a related field, or hands-on equivalent experience.

Additional Details

This opportunity comprises two fixed-term positions until 30 June 2027 with flexibility to work from any WorkSafe office location. Inter-agency secondments are considered; applicants should consult their managers beforehand.

Compensation and Benefits

The salary ranges from NZD 103,059 to NZD 135,004 annually, with KiwiSaver and SSRSS employer contributions added (KiwiSaver contribution increases to 3.5% from April 1, 2026). Benefits include:

• Five weeks of annual leave
• Fifteen days of sick leave
• Flexible working arrangements
• A Reward and Recognition Framework acknowledging impactful employee contributions
• Opportunities for professional growth
• Employee networks supporting diverse communities (Rainbow, Pacific, Women’s, and Tū Rangatira Māori)

Application Process

Applications require uploading a CV and cover letter. Candidates are encouraged to present their authentic skills, experience, and perspectives without overreliance on AI in application materials. Legal authorization to live and work in New Zealand is mandatory.

Organizational Context

The role aligns with WorkSafe’s organizational restructuring aimed at improved clarity, effectiveness, and role definition following an operational model review. Preference will be given to employees affected by these structural changes.

Application Deadline

Applications close at 11:59 PM on 21 September 2026. Early applications are recommended as the posting may close once preferred candidates emerge.