Associate - Assurance, Forensic - Data Analytics (2026 Graduates)

________

_________

The Opportunity:

EY Forensic & Integrity Services practice (“Forensics”) help organizations protect and restore enterprise and financial reputation. Our professionals assist companies and their legal counsel to investigate facts, resolve disputes and manage regulatory challenges. We put integrity at the heart of compliance programs to help better manage ethical and reputational risks. We understand how organizations navigate complex environments; how pressures, attitudes and culture influence employee actions; and how to leverage data analytics to improve compliance and investigation outcomes. We are committed to making integrity the cornerstone of a better working world. Our team is multi-disciplinary which includes amongst others, accountants, technologists, legal professionals, former law enforcement personnel, certified fraud examiners, data scientists, compliance professionals etc.

Our team has a specialty Forensic Technology group that has two main service lines: 1. Digital Forensics & Incident Response (DFIR) and Electronic Discovery (eDiscovery) Services and 2. Forensic Data Analytics (FDA). Our professionals apply a keen investigative mindset and strong IT, IT security and Data Analytics skills to help organizations investigate fraud, corruption, financial crimes, cybercrime or data breaches, alleged misconduct; conduct pro-active assessments to mitigate regulatory compliance and financial risks; and perform electronic evidence discovery in response to investigations, disputes or litigation. Our professionals are instrumental in collecting, analysing and presenting digital evidence to uncover all pertinent facts. Our Forensic Technology lab provides forensic technology infrastructure and tools necessary to accelerate the fact-finding process in diverse scenarios.

EY’s Forensic Data Analytics (FDA) practice is a global, data-focused team within the Forensic & Integrity Services (FIS) department. Our team supports clients in dealing with the complex issues of fraud, regulatory compliance, and business disputes. The FDA team practices the full life cycle of data analysis from the early stages of data discovery and capture to its management, analysis and reporting. Our engagements typically require working with large datasets from disparate sources to support investigations, disputes, and proactive risk detection.

Key responsibilities:

• Collect and analyse large volume of structured and unstructured data from a variety of data sources including ERP systems, accounting systems and others.
• Work with clients, fraud investigators, internal and external auditors, lawyers and regulatory authorities in sensitive situations and assist on conducting data analysis for identifying evidences of fraud, abuse and wastage.
• Analyse and mine the data using different analytical techniques to identify both known and unknown patterns of fraud
• Carry out both reactive and proactive data analysis of large datasets using a wide range of technologies, database management systems, business information reporting and visualisation software
• Ability to execute end-to-end lifecycle of the engagement - Data extraction, transformation, loading (ETL), analysis, visualisation, deployment and client delivery
• Adopt a problem-solving approach to overcome unexpected issues - both technical and operational.
• Prepare detailed working papers, schedules and reports.
• Present and communicate work procedures and findings clearly and to non-technical audiences
• Work under tight timelines and produce high quality deliverables.
• Keep abreast of latest developments in our field and actively contribute to innovation, development and documentation of new forensic technology solutions, procedures and workflows.

To qualify for the role, you must have:

• Degree in Computer Science, IT or related field
• Solid knowledge of SQL and a broad awareness of programming languages such as Python, R as well as Visualization techniques
• Strong verbal and written communication skills
• Ability to prioritize when working on multiple engagements
• Strong problem solving, analytical, technical, and interpersonal skills
• Ability to travel

Ideally, you’ll also have:

• Previous experience or knowledge of the below areas:
• Relational databases, e.g. SQL Server, PostgreSQL, Oracle, MySQL;
• Data visualisation software: Spotfire, Tableau, or Power BI;
• Azure/AWS cloud computing platform;
• Big data technologies such as Spark, Elasticsearch, Hadoop;
• Statistical techniques (regression, clustering etc.);
• Machine learning, pattern recognition, NLP etc;

Apart from the above, you should be able to demonstrate

• Ability to adapt confidently and quickly to changing environments, determination and tenacity to see the matter you are working on to its conclusion
• Skeptical yet practical mindset to assess situations and reach conclusions objectively.
• Proactiveness in sharing new knowledge and ideas to support achievement of shared vision.
• Strong communication skills and command over spoken and written English. Knowledge of another Asian language is valued, but not a requirement
• Strong analytical and problem-solving skills.
• Strong time, organization and prioritization skills
• Teaming and displaying strong interpersonal skills. Someone who is eager to learn, contribute and collaborate to support the achievement of a shared vision
• Self-awareness, respect for differences in individual style and background of your team members.
• Natural curiosity and ability to ask better questions

Note:

__________