Senior Data Scientist

About WorkSafe New Zealand

WorkSafe New Zealand | Mahi Haumaru Aotearoa is the principal regulator for workplace health and safety in New Zealand, aiming to ensure everyone returns home safe from work. The organisation operates under core values that foster unity, meaningful engagement, and duty of care.

Team and Role Overview

You will join the Enterprise Planning and Implementation group that enhances organisational planning and execution, focusing on prioritising and managing projects effectively. As part of the Data, Analytics and AI team, your work will underpin data-driven decisions, actively developing data foundations to support reporting, analytics, and organisational performance.

Key Responsibilities

• Develop, implement, and validate advanced analytical models and AI-driven solutions.
• Apply a range of statistical, machine learning, and AI techniques, including large language model-based strategies like retrieval-augmented generation, agents, and structured data extraction.
• Design evaluation frameworks for model outcomes by establishing test datasets, conducting human reviews, and selecting performance metrics.
• Facilitate the operational deployment of models and AI products, ensuring ongoing performance monitoring post-launch.
• Collaborate with data engineers, analysts, and stakeholders to deliver comprehensive end-to-end solutions.
• Enhance technical standards within the team through practices such as code reviews, reproducibility, documentation, and MLOps.
• Provide mentorship and technical guidance to junior data scientists.
• Effectively translate complex analytical results into actionable insights for decision-makers, clearly articulating capabilities and constraints of models.

Candidate Profile and Skills

• Extensive practical experience completing full-cycle data science projects, from defining problems and preparing data to modeling, validation, deployment, and monitoring in production environments.
• Proficiency in Python or R and SQL, with experience using key machine learning and data analysis libraries.
• Experience or a strong interest in large language model solutions such as RAG, AI agents, or structured extraction techniques, as well as classical machine learning methodologies.
• Strong expertise in model validation, understanding risks like data leakage, overfitting, and class imbalance, and selecting suitable evaluation metrics.
• Familiarity with cloud platforms, particularly Microsoft Azure, and knowledge of current MLOps practices.
• Capability to handle complex and large datasets, including incomplete or challenging data.
• Skill in communicating technical concepts, model limitations, and uncertainties clearly to non-technical stakeholders.
• Experience mentoring peers and enhancing the team's technical competencies.
• Relevant tertiary qualification in Data Science, Statistics, Mathematics, Computer Science, or related fields, or equivalent hands-on experience.

Salary and Benefits

The remuneration for this role ranges from NZD 120,551 to 158,328 per annum, with initial appointments expected between 120,551 and 133,143. Additional employer contributions to KiwiSaver/SSRSS apply, increasing to 3.5% from April 2026.

• Five weeks of annual leave
• Fifteen days of sick leave
• Flexible working arrangements
• Recognition frameworks celebrating individual contributions
• Opportunities for professional development
• Employee-led networks supporting diversity including Rainbow, Pacific, Women’s, and Tū Rangatira Māori groups

Additional Information

This position is part of an organisational restructuring aimed at improving role clarity and effectiveness. Preference will be given to current staff affected by these changes.

Applicants must have the legal right to live and work in New Zealand.

Applications close at 11:59 pm on 14th September 2026. Early applications are encouraged as the vacancy may be filled before the deadline.