Data Scientist — AI/ML for Regulatory Risk Analytics

Randstad Digital New Zealand; Auckland; On-site; NZD 103,000 - 135,000; Full time

Benefits offered by this job

5 weeks annual leave

15 days sick leave

Flexible working

Reward and recognition framework

Professional development

Diversity networks

Job summary

WorkSafe New Zealand is hiring a Data Scientist to apply advanced analytics, ML and AI to regulatory and organisational challenges. You will develop models and AI products with data engineers, analysts and stakeholders, informing decision-making and risk assessment.

The role focuses on risk-targeting projects and AI agents that support frontline and regulatory work, with a hands-on, produce-from-data mindset and a commitment to continuous learning.

Qualifications

• Proven hands-on data science project delivery from problem definition to deployment.
• Strong Python or R and SQL skills with core libraries.
• Experience with LLM-based solutions such as RAG, agents or structured extraction.

Responsibilities

• Design, build and validate advanced analytical models and AI solutions.
• Apply statistical, ML and AI techniques to complex problems and datasets (LLMs, RAG, agents).
• Design evaluation approaches for model outputs with test sets and human review.
• Support the transition of models and AI products into production and monitor performance.
• Partner with data engineers, analysts and specialists to deliver end-to-end solutions.
• Translate analytical findings into practical insights for decision-makers.

Skills

Python

SQL

R

LLM-based solutions

Communication

Cloud & MLOps

Education

Data Science/Statistics degree

Bachelor degree

Tools

Azure

Job description

WorkSafe New Zealand is hiring a Data Scientist to apply advanced analytics, ML and AI to regulatory and organisational challenges. You will develop models and AI products with data engineers, analysts and stakeholders, informing decision-making and risk assessment.

The role focuses on risk-targeting projects and AI agents that support frontline and regulatory work, with a hands-on, produce-from-data mindset and a commitment to continuous learning.