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The Forensic and Integrity Services team helps organizations safeguard their reputation and navigate complex challenges. We specialize in investigations, dispute resolution, and regulatory compliance, assisting companies and their legal counsel in uncovering facts and managing risks. Our integrated approach focuses on enhancing governance, controls, and data insights to restore financial and brand reputations, thereby building trust in capital markets worldwide.

This role focuses on forensic data analysis, leveraging strong SQL and data analytics skills to support investigations and risk assessments. You will be instrumental in extracting, transforming, validating, and analyzing large datasets to pinpoint anomalies, suspicious activities, control deficiencies, and potential misconduct.

Key responsibilities include: - Extracting and analyzing vast, intricate datasets using advanced SQL across diverse databases. - Performing data profiling, cleansing, transformation, and validation to ensure reliable analytical outcomes. - Crafting complex SQL queries with optimizations for performance. - Conducting forensic analytics to identify fraud indicators, unusual transactions, and behavioral patterns. - Integrating and reconciling data from various sources like ERP systems and databases. - Developing insightful dashboards and reports using visualization tools. - Documenting analytical processes, data lineage, and findings meticulously for audit trails.

The ideal candidate possesses excellent SQL proficiency, including complex querying and performance tuning, along with a solid understanding of relational databases, data modeling, ETL, and data quality principles. Hands-on experience analyzing high-volume transactional data is crucial.

We seek individuals with a strong analytical mindset, capable of identifying patterns, anomalies, and exceptions. Proficiency in Excel and Power BI is required, with Python for data analysis and automation being a desirable asset. Familiarity with databases such as SQL Server, Oracle, PostgreSQL, or Snowflake is beneficial.

Qualifications include a Bachelor of Technology in Computer Science, Bachelor of Computer Applications, or a certification in Data Analytics. Relevant postgraduate degrees such as Master of Engineering in Electronics, Master of Science in Data Science, or Master of Computer Applications are also considered.

We are looking for collaborative individuals with a practical approach to problem-solving, delivering insightful solutions. Agility, curiosity, mindfulness, and adaptability are key attributes. A minimum of 2 years of experience in Data Analysis is required. Experience in Machine Learning and Business Intelligence, with at least 3 years in each, is also necessary.