Fraud Data Scientist at ACC New Zealand

Wellington, Wellington, New Zealand -

Full Time

Start Date

Immediate

Expiry Date

31 Aug, 26

Salary

90418.0

Posted On

02 Jun, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, R, SQL, Power BI, Machine Learning, AI, Statistical Modelling, Fraud Detection, Data Analytics, Stakeholder Engagement, Cloud-based Analytics, Communication Skills

Industry

Government Administration

Description

* Wellington based permanent full-time role available in the Fraud Analytics team to prevent external fraud and misuse in ACC * Join an organisation that supports and develops your career * Enjoy building a supportive, inclusive and growth-set minded culture 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 [https://acc.co.nz]. About the role | Mō te tūranga mahi The Fraud Prevention and Investigation team prevent and address fraud, misuse, 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 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 misuse. You’ll use data science, machine learning and automation to transform complex, multi-source data into high-quality models, intelligence products and monitoring solutions that identify high-risk behaviours and enable effective interventions. You will work with Fraud Prevention & Investigation teams and wider stakeholders to translate complex challenges into actionable insights and practical tools. You’ll also contribute to a culture of integrity, innovation and partnership, applying technical skills, clear communication, and organisational values to deliver meaningful, real-world impact. 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: 1-3 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: Confident in Python, R, SQL, Power BI and cloud-based analytics environments, with capability or interest in machine learning, AI, and statistical modelling. * Fraud & Risk Insight: Experience working on fraud detection models, risk indicators, or advanced analytical tools that support prevention and early detection. * Communication Skills: Excellent interpersonal and communication skills (both verbal and written), and able to share insights from their analysis to a range of stakeholders. * Stakeholder Engagement: Confident in working with stakeholders. * 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 $77,502 - $90,418 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 As part of your application, please tell us in your cover letter: * Why do you want to be a data scientist in a fraud team? * If you are currently based outside Wellington, please clarify your willingness to relocate. * Describe your experience and proficiency using coding languages like SQL and Python. Applications will run through to 5:00 pm Sunday, 14th June 2026 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 [hrhelp@acc.co.nz].

Responsibilities

Develop advanced analytical tools and machine learning models to detect and prevent fraud and misuse within the ACC scheme. Translate complex data into actionable intelligence and monitoring solutions to support targeted investigations.