VP, First Party Fraud Business Analytics Lead Analyst

Job Description: VP, First Party Fraud Business Analytics Lead Analyst, London

This role is part of the Financial Crimes and Fraud Prevention organization, managing and executing first-party fraud analytics and strategies supporting Citi’s North American and global credit card businesses. Responsibilities include leveraging data to identify fraud trends, designing and implementing strategies to prevent and mitigate fraud across the full fraud lifecycle, including application and synthetic ID fraud, and sophisticated attack schemes.

Please ensure you read the below overview and requirements for this employment opportunity completely.

The role collaborates closely with Credit Risk Policy, Fraud Policy, Operations, Technology, and other partners to stay informed of business and technology developments and their potential fraud impacts.

Responsibilities:

• Utilize analytics to identify opportunities for enhancement and gain more detailed insights for action, ensuring compliance with Fraud Policy.
• Manage fraud rules, scores, detection strategies, risk appetite execution, POS interdiction strategies, and defect analysis.
• Work with cross-functional teams to provide strategic recommendations based on data and trend analysis, and implement mitigation strategies.
• Build effective relationships within and outside the Fraud organization to ensure timely execution of key portfolio priorities.
• Generate and oversee regular and ad-hoc reports to monitor and identify emerging trends.
• Assess manual and automated processes to identify gaps and opportunities.
• Lead analytical projects within the card first-party fraud analytics team, supporting the Card lines of business with advanced predictive and statistical techniques.
• Use customer data to develop risk segmentation and mitigation strategies, performing complex analyses to identify gaps and manage implementation across systems.
• Prioritize work and communicate clearly with partners and team members.
• Mentor and coach junior team members.

Qualifications:

• Bachelor’s Degree in statistics, mathematics, physics, economics, or related analytical discipline.
• 5+ years of experience in analytics and modeling or relevant fields.
• Extensive experience with Big Data environments, hands-on coding with traditional (SAS, SQL) and open-source (Python, Impala, Hive) tools, and knowledge of machine learning techniques such as Logistic Regression, Gradient Boosting, Random Forests, and visualization tools like Tableau.
• Strong quantitative and analytical skills to identify patterns, trends, insights, and perform risk/reward analyses.
• Ability to create effective presentations for diverse audiences.
• Proven ability to manage cross-functional projects, resources, and stakeholders, and to foster collaboration.
• Ability to make independent decisions with minimal guidance.

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