Business Analytics Senior Lead Analyst

In this role you will strategically develop and deploy fraud prevention rules and ML-driven scoring strategies to safeguard Citi Retail Services. You will partner with Fraud Retail Bank, Branded Cards, and Technology to shape a score-centric approach across the fraud lifecycle. You will lead data-driven analyses to identify patterns, present insights to executives, and mentor teammates to adopt robust rule development. This opportunity combines analytics, risk management, and cross-functional collaboration to reduce losses and enhance customer trust. A strong hook is your impact on scalable, sustainable decisioning through advanced analytics.

• medical, dental & vision coverage
• 401(k)
• life, accident, and disability insurance
• wellness programs
• paid time off
• paid holidays

• Own fraud rules, scores, detection strategies, risk appetite execution, and defect analysis.
• Document data requirements and perform data cleaning, processing, and exploratory analysis.
• Identify patterns and trends via exploratory, confirmatory, and qualitative analyses.
• Translate data into customer behavior insights to drive targeting and segmentation.
• Lead technical rule writing to deliver business value such as loss avoidance and improved CX.
• Recommend future developments and policy enhancements; introduce new tools and techniques.
• Assess processes for gaps and optimize decisioning for speed and sustainability.
• Build internal and external relationships to deploy and refine decision strategies.
• Collaborate with cross-functional partners to balance risk and return and drive accountability.
• Assess risk in business decisions, ensure compliance, and escalate control issues with transparency.

• 8+ years in fraud or risk management; analytics/modeling experience preferred.
• Extensive experience with Big Data; coding in SAS, SQL and/or open-source tools (Python, Impala, Hive).
• Experience with traditional and advanced ML techniques (Logistic Regression, Gradient Boosting, Random Forests).
• Data visualization experience (Tableau).
• Strong quantitative and analytical skills; ability to derive patterns and perform risk/reward analyses.
• Ability to present findings and influence executive audiences.
• Excellent communication, coaching, and mentoring abilities.

• excellent communication
• ability to influence executive audiences
• coaching and mentoring
• Big Data
• SAS
• SQL