Senior Fraud Data Scientist at Accident Compensation Corporation, Wellington
Mō tēnei tūranga mahi | About this role
About us | Mō mātou
ACC exists to support people - we help prevent injuries and get New Zealanders and visitors back to everyday life if they've had an accident.
You can find more about ACC and the work we do here.
About the role | Mō te tūranga mahi
The Fraud Prevention and Investigation team prevent and address fraud, abuse, and waste through intelligence-led action, timely intervention and appropriate remediation. Our Fraud Analytics team builds innovative solutions that turn complex data into actionable intelligence, enabling proactive detection, targeted investigations, and strategic interventions.
You'll be joining a supportive and collaborative team that values working together to achieve shared goals. We celebrate successes, learn from challenges, and actively support each other to improve. While we're a small but growing team, we bring a diverse range of experience and perspectives, creating an environment where knowledge is shared and innovation thrives. If you're looking for a place where teamwork and continuous development are at the heart of what we do, this is it.
As a Senior Fraud Data Scientist, you will play a key role in protecting the integrity of the Scheme by developing advanced analytical tools that detect, prevent, and respond to fraud and abuse. You'll lead innovation across the Fraud Analytics function - introducing cutting-edge statistical modelling, machine learning, and AI methods to build real-time, high-value solutions that enable early identification of suspicious behaviour at both individual and system levels.
You will work closely with Fraud Prevention & Investigation teams and wider stakeholders to translate complex challenges into actionable insights and practical tools. As a senior technical leader, you'll also coach data scientists and intelligence analysts, guide end-to-end project delivery, ensure strong governance across models and systems.
About you | Mōu
We're looking for proactive problem solvers who thrive off identifying trends, collaborating with others, and leveraging new and emerging technologies. We value potential and growth over perfection so if you meet most of the criteria and are enthusiastic about learning and contributing, we'd love to hear from you!
- Experience: 3-5 years of relevant professional experience, ideally in fraud prevention and detection, data analytics, or a closely related discipline.
- Education: Tertiary qualification in a relevant discipline or equivalent professional experience.
- Programming Skills: Strong proficiency in Python, R, SQL, Power BI and cloud-based analytics environments, with solid capability in machine learning, AI, and statistical modelling.
- End-to-End Delivery: Demonstrated ability to take data science products from concept to production, including modelling, testing, deployment, and optimisation.
- Leadership & Mentoring: Proven technical leadership, including coaching and developing data scientists or analysts.
- Stakeholder Engagement: Strength in translating complex analytical work into clear insights and building trusted relationships across business teams.
- Fraud & Risk Insight: Experience designing fraud detection models, risk indicators, or advanced analytical tools that support prevention and early detection.
- Project & Workflow Management: Strong organisational skills with the ability to manage multiple priorities in a fast-paced environment.
- Governance & Responsible AI: Familiarity with privacy, security, and ethical data frameworks, including responsible AI and secure production standards.
- Innovation Mindset: A proactive, curious approach with a strong focus on using data science and machine learning to drive innovation in fraud prevention.
- Cultural Competence: Understanding and application of Te Tiriti o Waitangi principles within data, analytics, and organisational decision-making.
This role requires you to be eligible to work in New Zealand.
Working at ACC | Mō ACC
At ACC, we embrace the rich tapestry of Aotearoa New Zealand's cultures and are dedicated to providing equitable opportunities. We know that a diverse and inclusive team helps us meet the needs of our customers, and we encourage applications from individuals of all backgrounds, ethnicity, national origin, gender identity, age, and those with diverse abilities. It is important to us that people are free to be themselves at work. Here are some ways we encourage that:
- Employee networks to support our colleagues from diverse backgrounds.
- The option to explore flexible working that suits your needs and ours.
The appointing salary for this role will sit between $101,287 and $119,161 and we offer an additional 9% superannuation contribution. ACC offer a comprehensive benefits package which at present includes an advantageous superannuation scheme with features like 0% contribution required by you, optional life and income protection insurance, and the flexibility to change to a locked plan at any time, ensuring your financial security now and in retirement.
How to apply | Me pēhea te tuku tono
Please attach your CV and cover letter telling us why you would be a great fit and what strengths you would bring to the role.
Applications will run through to 5pm Wednesday 21st January. However please note that if an ideal candidate is found during this time we will move forward with screening and interviewing sooner.
Applications can only be accepted when submitted through our ACC Career Website. If you encounter accessibility issues when submitting your application, or if you have any pātai (questions) about the role please email hrhelp@acc.co.nz
Ngā taipitopito tūranga mahi | Job details
| Employer: | Accident Compensation Corporation |
| Location: | Wellington |
| Position type: | Ongoing - Full Time |
| Category: | Data analytics |
| Date listed: | 07-Jan-2026 |
| Salary range: | |
| Closing date: | 21-Jan-2026 |
| Reference: | 1006046_1767749039 |
| Attachment: | No File Attached |
| File links: | |
| Website: | www.acc.co.nz |
Note: You may be redirected to the employer's careers website.