Senior Fraud Data Scientist

Fa Ernw Saasfaprod1; Wellington; On-site; NZD 101,000 - 130,000; Full time

Benefits offered by this job

9% superannuation

Comprehensive benefits

Job summary

ACC in Wellington, New Zealand, is seeking a Senior Fraud Data Scientist to lead analytical solutions that identify emerging fraud risks and suspicious behaviour at both individual and system levels.

You will apply advanced statistical modelling, machine learning, and AI techniques, while coaching data scientists and collaborating with investigators, prevention teams, and stakeholders to deploy end-to-end solutions from problem definition to production.

Qualifications

• Advanced SQL and Python capability within real business contexts.
• Experience applying ML/Statistical modelling to problems from ideation to deployment.
• Proven leadership, mentoring, and cross-priority delivery.
• Strong ability to translate analytical work into actionable insights for decision makers.
• Familiarity with privacy, security, and ethical data frameworks and responsible AI.

Responsibilities

• Lead development of high-value analytical solutions to identify emerging risks and suspicious behaviour.
• Apply advanced statistics, ML, and AI techniques to production-ready models.
• Coach and guide data scientists and analysts across priorities.
• Collaborate with investigators and prevention teams to deploy solutions from definition to production.

Skills

SQL

Python

Data science

Machine learning

Leadership

Stakeholder engagement

Problem solving

Education

Tertiary qualification

Job description

• Bring your technical leadership and practical experience to help us to deliver an ambitious work programme.

• Coach others and influence senior stakeholders to deliver impact for ACC.

• Join an inclusive, collaborative, innovative and high-performing team.

About the role | Mō te tūōnanga mahi

The Fraud Prevention and Investigation team works to prevent and respond to fraud, misuse, and waste through intelligence led action,timelyintervention, and effective remediation. Within this team, the Fraud Analytics function designs and delivers analytical products that turn complex data into actionable intelligence, supporting prevention activity, targeted investigations, and informed decision making.

You will join a supportive and collaborative team that values working together, shared learning, and continuous improvement. As a Senior Fraud Data Scientist, you will play a key role in leading the development of high value analytical solutions thatidentifyemerging risks and suspicious behaviour at both individual and system levels.

You will apply advanced statistical modelling, machine learning, and AI techniques to develop robustsolutions. Working closely with investigators, prevention teams, and a wide range of stakeholders, you will translate complex problems into practicalsolutionsthatenable effective action.

As a senior technical leader, you will provide coaching and guidance to data scientists and intelligence analysts, contribute to strong model and system governance, and take ownership of solutions from problem definition through to deployment and ongoing optimisation.

This is a permanent full-time opportunity, within the Fraud Prevention & Investigation team, based in Wellington.

About you | Mō

We’relooking for proactive problem solvers who thrivein collaborative environment and enjoys bringinginnovative ideas intoresults.

This role requires tertiary qualification in a relevant discipline - please submit your latest academic records or proof of tertiary qualifications.

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!

At least 3-5 years of practical experience applying data science or closely related field such as fraud detection & monitoring, risk analysis, or data/ analytics industry with a strong understanding of fraud detection approaches and indicators.

• Advanced SQL and Python capability, with demonstration of applying machine learning and/or statistical modelling in real business context, beyond theory or conceptual thinking.

• Demonstrated ability to deliver data science or analytical / automationsolutions end to end, from problem definition and modelling through to deployment, optimisation, and ongoing governance.

• Proven technical leadership, including mentoring and coaching analysts or data scientists, leading and delivering high-quality delivery across multiple priorities.

• Strong stakeholder engagement skills with the ability to translate complexanalytical work into clear, actionable insights that build trust and influence decision making.

• Demonstration of understanding / or experience in workingwithin privacy, security, and ethical data frameworks, including responsible AI and secure production standards with a continuous improvement mindset.

• 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 the role is between $101,287 and $129,885, and we offer an additional 9% superannuation contribution. ACC offers a comprehensive benefits package which at present includes an advantageous superannuation scheme with features like no mandatory employee contribution, 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.

Applications will run through till 11:59 pm Monday 26 October 2026, however if an ideal candidate is found we may progress screening and interviewing sooner.