Join a leading global professional services organization as a Senior Consultant in Forensics. This role is part of a dynamic national team focused on safeguarding and restoring corporate reputations.

You will contribute to high-impact investigations, compliance reviews, and risk analytics by leveraging your expertise in data extraction, transformation, and analysis. The position offers a unique opportunity to work across various industries, providing a well-rounded professional experience.

EY is committed to fostering a culture of continuous learning and development, offering personalized career journeys and abundant opportunities for growth. We believe in empowering our people to reach their full potential in a supportive and inclusive environment.

As a Forensics Data Analyst, you will be instrumental in extracting and analyzing large, complex datasets using advanced SQL. You will perform data profiling, cleansing, and validation to ensure reliable data for investigations.

Key responsibilities include developing sophisticated SQL queries, conducting forensic analytics to identify fraud and unusual patterns, and integrating data from diverse sources. You will also create visualizations and reports using tools like Power BI, ensuring thorough documentation of analytical processes and findings.

We are seeking candidates with a strong foundation in data analysis and SQL, supported by relevant academic qualifications and professional experience.

Essential qualifications include a Bachelor of Technology in Computer Science, Bachelor of Computer Applications, or equivalent. A Master of Engineering in Electronics, Master of Science in Data Science, Master of Computer Applications, or a Certification in Data Analytics are also highly valued.

Candidates should possess at least 2 years of experience in Data Analysis, 3 years in Machine Learning, and 3 years in Business Intelligence. Excellent SQL skills, proficiency in relational databases, ETL processes, and data quality concepts are mandatory. Experience with high-volume transactional datasets, a strong analytical mindset, and familiarity with tools like Excel and Power BI are crucial. Exposure to Python and databases such as SQL Server, Oracle, PostgreSQL, or Snowflake is desirable.