Fraud Analytics, Decisioning Lead

Role Overview

• Lead Digital Trust’s insights, measurement and fraud and scam modelling capabilities.
• Establish and maintain analytics, modelling and measurement practices that align with governance frameworks, regulatory obligations, risk requirements and data standards.
• Define performance measures, reporting frameworks and key indicators to monitor organisational, functional and project outcomes.
• Develop and enhance analytical models, reporting solutions and insight products that enable data-driven decision-making.
• Identify emerging risks, vulnerabilities and performance issues through analysis, driving appropriate mitigation and improvement actions.
• Translate strategic and operational priorities into analytical requirements, decision-support tools and actionable insights for senior stakeholders.
• Lead the design and implementation of analytics frameworks, methodologies and solutions that support business objectives and governance requirements.
• Drive continuous improvement through evidence-based recommendations, process optimisation and benefits-focused analysis.
• Provide trusted specialist advice to support operational leadership, informed decision-making and the effective execution of strategy.
• Build and maintain strong stakeholder relationships across AP+, industry participants, partners and vendors to influence outcomes and strengthen analytical capability.
• Lead team performance and capability development through coaching, mentoring and the promotion of continuous learning and analytical excellence.

Requirements

• Tertiary qualification in Data Analytics, Statistics, Mathematics, Economics, Business, Technology, Risk Management or a related discipline.
• Relevant professional certifications, or equivalent demonstrated experience, in analytics, modelling, measurement, risk management, quality management or continuous improvement are desirable.
• Demonstrated experience leading analytics, insights, performance measurement, modelling, fraud decisioning and operational performance functions within complex and highly regulated environments.
• Proven ability to influence and advise senior stakeholders, translating business objectives and data requirements into actionable insights, performance frameworks and decision-support solutions.
• Experience evaluating and managing vendor-provided analytics, modelling and technology solutions to ensure alignment with organisational objectives and operational requirements.
• Strong expertise in data analytics, performance measurement, governance, risk management, quality management and process improvement practices.
• Deep understanding of fraud and scam decisioning, including model design, development, implementation, monitoring, validation and performance optimisation.
• Advanced capability in SQL, Python, statistical analysis and data engineering, with the ability to derive insights from complex datasets and communicate findings effectively to both technical and non-technical audiences.
• Strong analytical and problem-solving skills, with the ability to identify risks, opportunities and emerging trends, and translate them into practical business outcomes.
• Sound understanding of governance, compliance and regulatory obligations relevant to data, analytics and risk management functions.

Tech Stack

• Python
• SQL