Business Analytics Lead Analyst, VP (Hybrid)

$113,840 - $170,760/Yr

Citigroup - Jacksonville, FL

Full-time - Senior

Jacksonville, FL

Credit Intermediation and Related Activities

About the position

The Business Analytics Lead Analyst, VP role at Citi involves managing and executing fraud analytics and strategies to support the North American and global credit card and retail bank businesses. The position focuses on leveraging data to identify fraud trends and designing strategies to prevent and mitigate fraud attacks across various fraud types. The role requires collaboration with multiple teams to ensure effective execution of fraud prevention strategies and involves mentoring junior team members.

Responsibilities

• Leverage analytics to identify enhancement opportunities and insights that can be acted upon, ensuring adherence to Fraud Policy.
• Ownership and management of fraud rules, scores, and detection strategies, including risk appetite execution and defect analysis.
• Collaborate with cross-functional teams to provide strategy recommendations based on data and trend analysis, and implement mitigation strategies.
• Build effective relationships within and outside the Fraud organization to ensure successful execution of key portfolio priorities.
• Generate and manage regular and ad-hoc reporting to monitor and identify emerging trends.
• Assess manual and automated processes to identify potential gaps and opportunities.
• Lead key analytical projects within the retail bank fraud and digital fraud analytics team, utilizing advanced predictive analytical techniques.
• Leverage customer data to build risk segmentation/mitigation strategies and manage implementation processes across systems.
• Prioritize and provide a clear line of sight to critical work for partners and team members.
• Mentor and coach junior team members.

Requirements

• Bachelor's Degree in statistics, mathematics, physics, economics, or other analytical or quantitative discipline.
• 5+ years of experience in analytics and modeling or a relevant area.
• Extensive experience with Big Data environments and hands-on coding in SAS, SQL, Python, Impala, Hive, etc.
• Experience with traditional and advanced machine learning techniques and algorithms, such as Logistic Regression, Gradient Boosting, Random Forests.
• Proficiency in data visualization tools, such as Tableau.
• Excellent quantitative and analytic skills to derive patterns, trends, and insights.
• Ability to build effective presentations to communicate analytical findings to diverse audiences.
• Effective cross-functional project and stakeholder engagement skills.

Nice-to-haves

• Master's degree preferred.
• Experience in fraud analytics or related fields.

Benefits

• Paid holidays
• Disability insurance
• Health insurance
• Dental insurance
• 401(k)
• Paid time off
• Vision insurance