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Associate Director - Forensic Data Analytics

Kpmgaustralia1·Worldwide·Brisbane, AU·mid
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About the Team KPMG’s Forensic practice supports clients in detecting and responding to fraud, misconduct, financial crime and regulatory breaches. The team works with organisations, regulators and legal advisors to investigate complex issues, resolve disputes and strengthen governance frameworks. By combining forensic expertise, advanced analytics and industry insight, the team helps organisations uncover the facts, quantify impacts and deliver defensible, data-driven outcomes across areas such as fraud, financial crime and customer remediation. Your Opportunity We are seeking an Associate Director to join our Forensic Data Analytics team in Brisbane. In this leadership role, you will lead teams of analysts to solve complex client challenges across investigations, remediation and dispute matters. You will play a key role in translating business and legal requirements into data-driven solutions, enabling clients to identify issues, quantify financial impacts and present clear, evidence-based findings. This is a high-impact role offering exposure to varied projects, from short-term investigations to large-scale transformation programs, working with leading organisations, regulators and legal firms. How are you Extraordinary • Analytical thinker: Able to break down complex problems and translate them into clear, structured insights • Collaborative leader: Builds strong relationships and leads multidisciplinary teams to deliver quality outcomes • Clear communicator: Presents complex data and findings in a concise and meaningful way to diverse audiences Key Responsibilities • Lead forensic data analytics engagements across fraud, financial crime, remediation and investigation matters • Translate business and legal requirements into analytics methodologies and data models • Develop and execute data analysis using tools such as SQL and Python to identify anomalies and insights • Quantify financial impacts using codified business rules and structured analytical approaches

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