Description

You will execute the full lifecycle of forensic data analysis to support investigations, regulatory compliance, and fraud detection.

This role is on-site.

Responsibilities

• Analyze and mine large structured and unstructured datasets from ERP and accounting systems to identify patterns of fraud, abuse, and misconduct.
• Develop algorithms and technical solutions to detect, prevent, and monitor financial crime and bribery.
• Execute end-to-end ETL processes, including data extraction, transformation, loading, analysis, and deployment.
• Create visualization materials to present analytical findings and complex concepts to clients, lawyers, and regulatory authorities.
• Collaborate with fraud investigators and auditors to conduct both reactive and proactive data analysis.

Required Skills

• 5+ years of professional experience in data analytics or a related field.
• Proficiency in SQL and experience with relational databases including SQL Server, PostgreSQL, Oracle, or MySQL.
• Strong understanding of algorithms and data mining techniques.
• Experience with programming languages such as Python or R.
• Ability to use data visualization techniques to communicate complex findings.
• Degree in a STEM discipline (Computer Science, Engineering, Statistics, Mathematics) or equivalent work experience.
• Strong documentation skills and the ability to manage multiple engagements simultaneously.
• Excellent communication skills for explaining technical concepts to non-technical stakeholders.

Preferred Skills

• Experience with visualization software such as Spotfire, Tableau, or Power BI.
• Knowledge of cloud platforms (Azure/AWS) or big data technologies like Spark, Elasticsearch, or Hadoop.
• Background in statistical techniques, machine learning, pattern recognition, or NLP.

Key Skills

Education

Any Graduate