remote
Consultant, Financial Crimes - Data Analytics - KPMG
Software Engineer
Lead data analytics initiatives to detect and prevent financial crimes, leveraging Python, SQL, and machine learning to uncover patterns, support regulatory compliance, and drive actionable insights for clients.
About the role
Key Responsibilities
- Design, develop, and maintain data pipelines and analytical models to identify money laundering, corruption, and emerging financial crime threats.
- Apply advanced statistical and machine learning techniques in Python to uncover hidden patterns and risk indicators.
- Collaborate with cross‑functional teams to translate regulatory requirements into data‑driven solutions.
- Generate clear, actionable insights and visualizations for senior stakeholders and clients.
- Stay current on industry regulations, emerging threats, and best practices in financial crime analytics.
Requirements
- Proven experience in data analytics, preferably in financial crime or compliance environments.
- Strong programming skills in Python and proficiency with SQL for data extraction and manipulation.
- Hands‑on experience with machine learning libraries (scikit‑learn, TensorFlow, etc.) and data visualization tools.
- Deep understanding of regulatory frameworks such as AML, FATF, and related compliance standards.
- Excellent communication skills and ability to present complex findings to non‑technical audiences.
Skills
pythonsqlmachine learning