Lead Data & Insights Strategist for Policy Impact

Ministry for Pacific Peoples; Wellington; In loco; NZD 110.000 - 166.000; Tempo pieno

Vantaggi offerti da questo lavoro

Healthcare insurance

Subsidised eye care

Three extra annual leave days

Descrizione del lavoro

Ministry for Pacific Peoples seeks a Principal Analyst Data to lead complex analysis and provide technical leadership across the Ministry, informing policy and government decisions with robust evidence. You will work with large datasets including IDI and administrative data, designing rigorous research and turning results into clear insights for decision-makers.

You will lead QA, develop reproducible code, improve automation, explore responsible AI, and coach staff while building strong

Competenze

• Strong record in quantitative analysis, research and evidence-based advice.
• Experience with large, complex datasets and IDI or linked administrative data is desirable.
• Ability to design robust quantitative research and turn findings into decision-ready insights.

Mansioni

• Lead complex analytical work and provide technical leadership across the Ministry.
• Design robust quantitative research and turn findings into clear, decision-ready insights.
• Oversee QA and develop reproducible code and robust workflows.
• Improve automation and explore responsible uses of AI.
• Partner across government and coach staff to strengthen data capability.

Conoscenze

Quantitative analysis

Large datasets

SQL

Python

R

Code reproducibility

Version control

QA/testing

AI awareness

Formazione

Quantitative degree

Strumenti

IDI data

SQL

Python

R

Descrizione del lavoro

Ministry for Pacific Peoples seeks a Principal Analyst Data to lead complex analysis and provide technical leadership across the Ministry, informing policy and government decisions with robust evidence. You will work with large datasets including IDI and administrative data, designing rigorous research and turning results into clear insights for decision-makers.

You will lead QA, develop reproducible code, improve automation, explore responsible AI, and coach staff while building strong