Customer Monitoring and Detection Analytics Manager Job in Bengaluru at ANZ Banking Group

ANZ Banking Group is hiring for the role of Customer Monitoring and Detection Analytics Manager!

Responsibilities of the Candidate:

• Quantitative Tuning & Monitoring Deployment: Lead the quantitative tuning of Automated Transaction Monitoring (TM) scenarios, ensuring the models are finely tuned for accuracy. Oversee the deployment and monitoring of these models to continuously enhance their effectiveness.
• Team Leadership: Drive continuous improvement by leading a GCC team of analysts, fostering a collaborative environment to optimize model performance and compliance.
• Stakeholder Engagement: Engage with stakeholders, including in-country Money Laundering Risk Officers, Model Validation teams, and Financial Crime Coverage teams. Facilitate clear communications to ensure alignment on model performance and risk coverage.
• Data Integration: Translate financial crime red flags into actionable data features. Oversee data processing steps to ensure high-quality data inputs for model development and performance evaluation.
• Documentation & Compliance: Develop and maintain thorough documentation outlining model purposes, development details, data usage, sampling methods, methodology, assumptions, limitations, and operational controls. Ensure documentation supports Model Validation requirements.
• Operational Controls & Monitoring: Define and maintain appropriate monitoring performance standards and metrics. Ensure models operate within established limitations and usage boundaries to adhere to compliance and operational risk standards.

Requirements:

• Relevant Experience: Financial Services experience with a growth mindset to rapidly learn and enhance Financial Crime knowledge. A strong understanding of AML Transaction Monitoring or Customer Risk Scoring solutions is highly regarded.
• Communication Skills: Exceptional written and verbal communication skills, capable of conveying complex issues clearly and succinctly.
• Prioritization & Influence: Strong ability to manage priorities professionally, with influential skills to drive consensus and implementation.
• Technical Expertise: Outstanding problem-solving abilities with meticulous attention to detail. Expertise in Python and SQL, with a track record of writing clean, modular, and reusable code. Practical experience in deploying machine learning algorithms, including data pre-processing, feature engineering, and continuous model training and evaluation.
• Educational Background: Bachelor’s or Master’s degree in Data Science, Computer Science, Mathematics, Statistics, or a related field.
• Cloud Platforms: Practical experience deploying solutions on cloud platforms such as GCP, AWS, or Azure preferred.
• Governance Knowledge: Experience with technology and process governance requirements when deploying solutions.