Forensic Data Analytics, Manager / Associate Director

Job Description

KPMG's Forensic practice consists of experienced professionals with a wealth of experience in investigations, AML/CTF, data analytics, FATCA/CRS, forensic technology and disputes.

We help clients deal with:

• Fraud, misconduct and corruption investigations
• Assess and improve client’s AML controls and financial crime compliance
• Commercial disputes
• Regulatory compliance
• Managing risk on buying or selling a business, intellectual property and contract governance
• Preventing and detecting fraud and financial crime
   

We also deploy technology tools to help clients deal effectively with large amounts of data and documentation, to manage and disclose important material or highlight fraud, weaknesses and business opportunities from within corporate data. The Forensic Data Analytics team combines data, technology, and analytics to deliver investigative and compliance solutions. We build and deploy analytical tools and dashboards across industries, integrating technical capability with business understanding.
 
As a Manager/Associate Director in the Forensic DA team, you will lead AML compliance and financial crime analytics across the financial services sector. This is a client-facing, delivery-led role with direct responsibility for project management, team development, design and implementation of data-driven solutions in financial crime compliance processes such as transaction monitoring and name screening.
 
The candidate will bring about his/her technical expertise in advanced analytics, knowledge in AML domain, and interpersonal skills to manage senior client stakeholders and lead project teams. You will have also the opportunity to ideate and test innovative approaches such as applying large language models and agentic AI to deliver value adding services for our clients.

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Your scope of work will include:

AML System Validation and Calibration

• Conduct and lead independent validation and calibration exercises for AML transaction monitoring and name screening system including, data lineage testing, rule effectiveness testing, threshold calibration for financial institutions
• Present validation findings and remediation recommendations to stakeholders such as compliance teams, and senior management 

Data Analytics & Financial Crime Investigations

• Apply data analytics techniques to identify anomalies, and surface patterns indicative of money laundering, fraud, or other financial crime typologies
• Design and develop analytical models, including statistical, machine learning, and rules-based approaches to support AML detection and monitoring 
• Build and maintain data pipelines, perform data cleaning and transformation, and conduct exploratory analysis using tools such as Python, SQL, and Excel.
• Develop dashboards and visualisations to communicate analytical findings and compliance metrics to both technical and non-technical stakeholders

AML Advisory & Regulatory Compliance

• Demonstrate working knowledge of key AML concepts including transaction monitoring , customer due diligence , know-your-customer, name screening, suspicious transaction reporting, and AML typology analysis
• Stay current with regulatory developments including MAS AML/CFT requirements, FATF guidance, and regional best practices and incorporate these into client deliverables and communication

Project Management & Delivery

• Manage end-to-end delivery of client engagements, including project scoping, workplan development, team coordination, and reporting
• Lead and develop the DA team, providing day-to-day direction, technical coaching, and performance feedback
• Manage client relationships proactively such as anticipating needs, communicating progress, and escalating issues timely 
• Prepare and review client deliverables including reports, presentations, and working papers to maintain a high standard of quality and accuracy

Business Development

• Contribute to KPMG's business development efforts in the financial crime space by identifying new opportunities within existing client relationships and the broader market
• Support the preparation and delivery of proposals and pitch presentations for prospective clients
   

Qualifications and Experience:

• Around 7 years of relevant experience in AML compliance, financial crime analytics, forensic accounting, or a related field
• Strong understanding of AML/CFT concepts, typologies, and regulatory frameworks, including transaction monitoring, name screening, CDD/KYC and AML system governance
• Proficiency in data analytics tools including SQL, Python and Tableau/Power BI for data extraction, analysis, and reporting
• Strong written and verbal communication skills, with the ability to present complex findings clearly to senior and non-technical stakeholders
• Exposure to machine learning techniques applied to financial crime detection (e.g. supervised classification, anomaly detection, clustering)
• Demonstrates interest with emerging technologies in the AML compliance domain, including large language models or other AI-assisted review tools.
• Demonstrated ability to manage multiple workstreams and deliver high-quality outputs under time pressure

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