Citi Group Director Head AML Data Science Model Management Hybrid 

United States, New Jersey 

661504994

AML NAM Head of Data Science and Model Managementis a strategic professional who closely follows latest trends in own field and adapts them for application within own job and the business. Recognized subject matter expert within one area. Strong commercial awareness is a necessity. Is an acknowledged authority both within and outside area of expertise. Typically a small number of people within the business that provide the same level of expertise. Excellent communication skills required in order to negotiate internally, often at a senior level. Some external communication is typically required. Provides advanced judgment and conducts in-depth quantitative or qualitative analysis to solve problems and develop new, innovative solutions. Required to think beyond existing solutions, assumptions or current knowledge of sophisticated areas. Significant impact on a function and/or the business through making decisions that determine technical approaches and strategies for the area.Responsibilities:

• Design, develop, deliver, and maintain best-in-class AML Compliance policies and practices; provide a mechanism for identifying key money laundering risks and how the mitigation of those risks would be monitored and measured through a robust control framework. Conducted reviews consistently across each entity on a regular basis to confirm that the controls identified are operating effectively.
• Develop and improve upon the Governance and Escalation framework to inform senior management in a timely manner of emerging issues for promptly action and correction.
• Establish a formal Feedback Channel with the Businesses, Internal Audit and Compliance Assurance to validate that root cause analysis is performed proactively and communicated to relevant stakeholders through the established channel. In addition, review, consolidate, address, and track to resolution significant issues identified through root cause analysis to senior management. Furthermore, confirm that the feedback / root causes from various channels is consolidated and shared within Compliance to allow for enhancements to Policy/Standards and Learning & Development, as necessary.
• Continually review and monitor the results from Manager Control Assessments (MCAs) to determine if changes are required.
• Liaise with US and foreign regulators externally and Citi Internal Audit and Compliance Assurance staff, as appropriate, including coordinating AML-related examinations, audit and reviews, document production, and issue responses - to confirm that there is consistency in responses and issues are communicated across regions, such that actions and conclusions are shared.
• Provide adequate training to the Business lines and other AML Compliance employees, and, as needed, participate in the design and delivery of training as required, to inform employees of the objectives of the program.
• Engage a diverse team of staff across multiple locations; invest in the development of all team members to facilitate consistent execution.
• Additional duties as assigned.
• Appropriately assess risk when business decisions are made, demonstrating particular consideration for the firm's reputation and safeguarding Citigroup, its clients and assets, by driving compliance with applicable laws, rules and regulations, adhering to Policy, applying sound ethical judgment regarding personal behavior, conduct and business practices, and escalating, managing and reporting control issues with transparency.

Qualifications:

• 15+ years relevant experience
• AML certification
• Prior work experience in a financial institution with job specific work experience in AML
• Self-motivated and detail oriented
• Consistently demonstrates clear and concise written and verbal communication skills
• Advanced presentation skills with the ability to articulate complex problems and solutions through concise and clear messaging Significant knowledge and expertise of AML regulations, risks and appropriate controls Experience in the design and implementation of AML programs
• Demonstrated ability to assess complex issues through root cause analysis and other analytical techniques; structure potential solutions; drive to resolution with senior stakeholders
• Ability to influence and lead people across cultures at a senior level using sound judgment and successful execution, understanding how to operate effectively across diverse businesses
• Experience with and previous exposure to internal or external control functions and regulators (incl. the US); particularly banking and AML regulators
• Level of comfort with creative tension across different lines of defense while maintaining professionalism and a shared goal of increased quality levels across the program
• Demonstrated ability to effectively assessing and managing competing priorities Experience managing diverse teams, and comfort navigating complex, highly-matrixed organizations Knowledge of the laws applicable to money laundering, including the Bank Secrecy Act, The USA PATRIOT Act, US Treasury AML guidelines, OFAC requirements, and Suspicious Activity Reporting requirements

Education:

• Bachelors (4 Year University) Degree or equivalent experience is required
• Masters Degree preferred

The NAM Head of Data Science and Model Management leads teams of senior compliance professionals in the design, development, and defense of AML detection models. The role requires a broad and comprehensive understanding of the different systems, theories and practices relevant to AML risk mitigation though statistical analysis and machine learning, as well as practical experience across multiple first line business functions.

In-depth knowledge of the industry and direct competitors' products/services is also necessary in order to contribute to the commercial objectives of the Financial Crimes Compliance area including, but not limited to AML, Sanctions, Anti-Bribery, KYC, Fraud, and Cyber. Requires thorough understanding of strategic direction of the AML function in support of business execution activities, combined with a solid conceptual/practical grounding in both AML and data science risks and control development activities.

Anticipated Posting Close Date:

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