Associate - Forensic Data Analyst (2024 Graduates)

What if your curiosity could help build the world we all imagine?

Here at EY, you’ll have the chance to build a truly exceptional experience. We’ll empower you with the latest technology, surround you with high-performing teams, and provide the global scale and diverse and inclusive culture you need to discover your full potential. Through our coaching and training programs, you’ll develop the skillsets you need to stay relevant today and in the future – all while building a network of colleagues, mentors, and leaders who will be on the journey with you at EY and beyond.

The exceptional EY experience. It's yours to build.

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The opportunity: your next adventure awaits



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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.

Since we work with such a diverse portfolio of clients across industries, you can expect to take on a wide range of technology challenges, making this a great place to develop your technical and business knowledge. Our Forensic Technology lab provides forensic technology infrastructure and tools necessary to accelerate the fact-finding process in diverse scenarios.

Key responsibilities:

• 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
• Collect and analyse a large amount of structured and unstructured data from a variety of data sources including ERP systems, accounting systems and others.
• 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
• Develop algorithms and solutions to detect, respond, prevent, continually monitor and investigate areas of fraud, bribery & corruption, misconduct and financial crime
• Develop supporting material using a suite of visualisation software to clearly present the benefits of the analysis to clients
• Execute end-to-end lifecycle of the engagement - Data extraction, transformation, loading (ETL), analysis, visualisation, deployment and client delivery
• Align to various strategic teams in the areas of technology and innovation

To qualify for the role, you must have:

• Strong academic qualifications with a degree in a STEM discipline (Computer Science, Engineering, Statistics, Mathematics, etc.) or equivalent work experience
• Demonstrate proficiency in SQL and a broad awareness of programming languages such as Python, R as well as Visualization techniques
• Strong problem solving, analytical, technical, and interpersonal skills.
• Strong critical thinking, problem-solving skills, understanding of algorithms and appreciation of working with data
• Excellent communication skills and ability to explain complex analytical concepts to stakeholders from different backgrounds
• Excellent documentation skills with the ability to prioritize when working on multiple engagements.
• The ability to travel to client locations.

Ideally, you’ll also have:

• Previous consulting experience and experience with any of the below areas would be an added benefit:
  • 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;

We are looking for tenacious and curious individuals with a desire to ‘get to the bottom’ of things. You will be intellectually rigorous, with extremely strong analytical skills, have a passion for data, be adaptable and show an ability to build strong relationships.

For your application to be considered, please upload both your resume and transcript.



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Please note that applications are shortlisted on a rolling basis. We regret to inform that only shortlisted candidates will be notified.

To learn more about careers in EY, please visit Careers at EY or connect with us on social media (Facebook or Instagram) to hear from our people about their EY careers.

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