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Financial Crimes Model Analytics Manager - Truist Bank
Software Engineer
Lead the development and deployment of advanced analytics models to detect and prevent financial crimes, leveraging Python, SQL, and AWS to deliver scalable, high‑impact solutions.
About the role
Key Responsibilities
- Design, build, and maintain predictive models for fraud detection and financial crime prevention using Python and SQL.
- Collaborate with cross‑functional teams to define data requirements, feature engineering, and model validation strategies.
- Deploy models to production on AWS, ensuring scalability, reliability, and compliance with regulatory standards.
- Monitor model performance, conduct root‑cause analysis, and implement continuous improvement cycles.
- Communicate findings and insights to stakeholders through clear visualizations and executive summaries.
Requirements
- 5+ years of experience in data science or analytics within the financial services sector.
- Proficiency in Python, SQL, and AWS services (SageMaker, Lambda, Redshift).
- Strong background in machine learning techniques, model evaluation, and feature selection.
- Experience with fraud detection frameworks and regulatory compliance (e.g., AML, KYC).
- Excellent problem‑solving skills and ability to translate complex data into actionable insights.
Skills
pythonsqlmachine learningaws