Forensic Data Analytics Graduate Programme
@ EY

London, England, United Kingdom
£50,000
On Site
Full Time
Posted 21 days ago

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Job Details

Programme Overview

The Forensic Data Analytics Graduate Programme at EY offers an opportunity to investigate, analyse, and uncover patterns in massive datasets to resolve fraud, regulatory, and compliance issues. As a graduate, you will work with the latest data tools and technologies to tackle sensitive challenges such as price fixing, misappropriation of funds, employee misconduct, and financial crime.

Our team utilises tools like Spark, Scala, SQL, Python, and Alteryx to process data on-premise or in the Cloud. Using various Data Science models and techniques, you will identify behaviours of non-compliance or fraud and present findings to stakeholders through reporting tools such as Power BI.

What You Will Be Doing

  • Identify, receive, and construct large composite datasets.
  • Solve client issues using advanced analytical tools and techniques including neural networks and natural language processing.
  • Design and develop modular, reusable solutions on cutting-edge platforms.
  • Gain domain knowledge by working with diverse sectors and understanding forensics including Anti Money Laundering, Counter Terrorism Financing, Sanctions, Fraud, and Compliance.
  • Present findings in compelling stories using modern visualisation tools.

Key skills/competency

  • Data Analysis
  • Fraud Detection
  • Data Science
  • Forensics
  • Python
  • SQL
  • Spark
  • Scala
  • Alteryx
  • Power BI
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How to Get Hired at EY

🎯 Tips for Getting Hired

  • Tailor your resume: emphasize data analytics and forensic experience.
  • Showcase technical skills: highlight Spark, Python, SQL proficiencies.
  • Research EY culture: explore their mission, values, and success stories.
  • Prepare for interviews: practice case studies and technical questions.

📝 Interview Preparation Advice

Technical Preparation

Review Spark and Scala basics.
Practice SQL queries and Python scripts.
Study forensic data models.
Learn modular data solution design.

Behavioral Questions

Describe a challenging data problem solved.
How do you handle teamwork under pressure?
Explain learning from a project failure.
Discuss adapting to new technologies quickly.

Frequently Asked Questions