Embark on a career in forensics and investigations with a global leader dedicated to building a better working world. EY's Forensics & Integrity Services professionals safeguard and restore enterprise and financial reputations. This role offers a unique opportunity to work with organizations and legal counsel on complex investigations, dispute resolutions, and regulatory challenges, ensuring integrity at the core of compliance programs.

This position is part of National's sector-agnostic teams, providing a well-rounded experience across various industries. The ASU - Forensics - Investigations & Compliance team focuses on helping companies manage ethical and reputational risks, enhancing governance, controls, and data insights to protect and restore financial and brand reputations worldwide.

As an Associate Consultant in Forensics, you will play a key role in supporting eDiscovery engagements. Your responsibilities include preparing, organizing, and quality-checking data for processing, review, and analysis. You'll utilize Python to automate repetitive tasks, assist with AI-enabled workflows like document classification and entity extraction, and work with structured and unstructured datasets to identify quality issues.

Further duties involve supporting data ingestion, culling, and search activities in eDiscovery platforms, along with testing scripts and analytical outputs. You will maintain reproducible workpapers and prepare clear presentations summarizing methodologies, results, and limitations for project teams.

To excel in this role, you should possess a B.E./B.Tech./M.Tech./M.Sc. or equivalent degree in Computer Science, AI, Data Science, Information Technology, or a related field, supported by a good academic record. Demonstrable coursework or projects in Python, AI, machine learning, NLP, or data analytics are essential.

We are looking for candidates with 1-2 years of relevant experience, which can include internships, capstone projects, research, hackathons, or college projects. Foundational knowledge of Python, including libraries like pandas and NumPy, is required, alongside a basic understanding of SQL, data structures, algorithms, and statistics. Strong written and verbal communication skills are also crucial.