Fuku

Data Analyst Group Internal Audit

Fuku Kuala Lumpur, Kuala Lumpur, Malaysia

Retail Apparel and Fashion · 2-10 employees

4 h ago
data-analyst Mid (2-5 yrs) Full-time Malaysia
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About the role

The Data Analyst will design and execute data-driven audit procedures to identify high-risk transactions and control exceptions. They will also create interactive dashboards and automated workflows to communicate audit findings and improve team efficiency.

What they look for

Data Analysis Internal Audit Statistical Analysis Data Visualization Anomaly Detection Trend Analysis Audit Analytics Automation Dashboarding Forensic Analysis Risk Assessment ERP Systems Data Modeling Stakeholder Management Financial Services Process Improvement

Requirements

The role requires a skilled professional with strong analytical capabilities and experience in internal audit or data science. Candidates should be proficient in extracting data from ERP systems and translating complex datasets into actionable business insights.

Full description

About Hytech Hytech is a leading management consulting firm headquartered in Australia and Singapore, specialising in digital transformation for fintech and financial services organisations. The company delivers end-to-end consulting services and robust middle- and back-office solutions, enabling clients to optimise operations, enhance efficiency, and stay ahead in a fast-evolving digital landscape. Hytech’s client portfolio includes top global trading platforms and leading crypto exchanges.

With more than 2,000 professionals worldwide, Hytech has a strong and growing international presence, with offices across Australia, Singapore, Malaysia, Taiwan, the Philippines, Thailand, Morocco, Cyprus, Dubai, and beyond.

Position Overview Hytech is seeking a skilled and analytically-minded Data Analyst to strengthen its Group Internal Audit function. This role combines technical data expertise with audit acumen to transform complex datasets into actionable insights, driving more effective and efficient audits across the organization. The Data Analyst will work at the intersection of data science and internal audit, designing data-driven audit procedures, building analytics frameworks, and presenting compelling visualizations to senior leadership. This is a high-impact position that influences audit strategy and control recommendations across the entire group.

Key Responsibilities Audit Analytics & Data-Driven Procedures (40%) - Extract, clean, and analyze data from multiple sources (ERP systems, databases, data warehouses) to support audit planning and fieldwork. - Design and execute statistical audit procedures including sampling, anomaly detection, and trend analysis to test control effectiveness. - Develop data-driven audit programs that identify high-risk transactions, unusual patterns, and control exceptions. - Perform forensic-style analysis to investigate control failures and potential fraud indicators.

Data Visualization & Reporting (30%) - Create interactive dashboards and compelling visualizations to communicate audit findings to senior management and audit committees. - Build audit metrics dashboards for real-time monitoring of key control indicators and audit progress. - Translate complex data analyses into clear, business-focused narratives and executive presentations. - Maintain detailed documentation of audit analytics methodologies to support audit trail requirements.

Analytics Automation & Process Improvement (20%) - Identify opportunities to automate routine audit procedures through analytics tools and scripts. - Develop repeatable audit templates and workflows to improve team efficiency and consistency. - Build audit data models and maintain reusable analytics frameworks across audit engagements. - Recommend enhancements to audit scopes based on data patterns and emerging risks.

Stakeholder Collaboration & Support (10%) - Partner with business unit leaders to understand data requirements, control environments, and audit scope. - Collaborate with IT and Finance teams to ensure data access, accuracy, and system integration. - Mentor junior audit staff on data analytics techniques and best practices. - Present findings and recommendations to audit committee members and senior leadership.

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