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This Associate Consultant role within the National Forensics Investigations & Compliance team in Bangalore offers a chance to work across diverse industries. EY Forensic & Integrity Services professionals safeguard and restore enterprise reputations by assisting organizations with investigations, dispute resolution, and regulatory challenges. We help build trust and confidence in capital markets by embedding integrity into compliance programs and mitigating ethical and reputational risks.

Support eDiscovery engagements through meticulous data preparation, organization, and quality checks for processing and analysis. Automate repetitive data tasks using Python, including preparation, validation, file handling, and reporting. Assist with AI-driven workflows like document classification, clustering, entity extraction, and review prioritization. Analyze structured and unstructured datasets, identify data quality issues, and document transformation processes. Participate in data ingestion, culling, search, review preparation, and quality control within eDiscovery platforms. Test analytical scripts, document assumptions, and maintain reproducible workpapers. Prepare clear presentations summarizing methodologies, results, and limitations for project teams.

Possess fundamental Python skills, including pandas, NumPy, regular expressions, and file/data handling. Have a foundational understanding of machine learning, natural language processing, generative AI concepts, and responsible AI usage. Demonstrate basic proficiency in SQL, data structures, algorithms, statistics, and analytical problem-solving. Exhibit strong written and verbal communication, along with effective presentation skills.

Qualifications include a recent B.E./B.Tech./M.Tech./M.Sc. or equivalent degree in Computer Science, AI, Data Science, Information Technology, or a related field. A good academic record and demonstrable coursework or projects in Python, AI, machine learning, NLP, or data analytics are essential. Experience: 1-2 years of relevant experience, including internships, capstone projects, research, hackathons, or college projects, will be considered practical experience. Exposure to eDiscovery, RelativityOne, scikit-learn, Jupyter notebooks, APIs, Power BI, or cloud AI services is advantageous but not mandatory. Ability to explain academic AI/Python projects end-to-end is highly valued.