Data Analyst – Merchant and Loyalty Rewards Integrity, AVP

Location: Jacksonville, Florida, United States, San Antonio, Texas, United States, O'Fallon, Missouri, United States, Tampa, Florida, United States, Florence, Kentucky, United States, Johnson City, Tennessee, United States, Sioux Falls, South Dakota, United States, Irving, Texas, United States, New Castle, Delaware, United States

Employment Type: Regular

Data Analyst – Merchant and Loyalty Rewards Integrity

The Data Analyst Merchant and Loyalty Rewards Integrity role is responsible for identifying, analyzing, and quantifying emerging fraud risks impacting merchant authenticity, business impersonation, and the loyalty rewards ecosystem. This role drives deep dive analysis to uncover fraud abuse trends, quantify exposure, and inform detection and prevention strategies across the enterprise. This position partners closely with Data Scientists, Detection Team, Fraud Strategy, Product, Intelligence, and Risk Teams to transform complex behavioral signals into actionable risk insights that protect the integrity of merchant onboarding, merchant activity, and loyalty programs.

Responsibilities:

• Conduct deep-dive analytics into suspicious merchant behavior patterns to identify indicators of business impersonation, inauthentic merchants, dormant merchant take-over, and merchant account mule networks. Analyze merchant lifecycle behavior from onboarding through transaction activity.
• Quantity financial, operational, and reputational risk exposure.
• Produce structured analysis summaries for leadership and risk governance.
• Analyze rewards issuance, redemption, and transfer behaviors to detect points farming, promotion abuse, referral manipulation, account cycling, manufactured spend, and collusive merchant behavior.
• Identify emerging abuse typologies across travel, dining, retail, and digital marketplaces ecosystems.
• Quantify abuse rates, loss trends, and concentration risk.
• Deliver actional insights that inform rule creation and model features.
• Perform micro and macro-level portfolio analysis to detect behavioral shifts, coordinated abuse, cross-channel risk patterns, and geographic or fingerprint clustering.
• Use advanced SQL, Python, or analytical tooling to segment risk populations, identify anomaly cohorts, detect early indicators of exploitation.
• Develop recurrent reporting frameworks for emerging threats.
• Translate analytical findings into feature recommendations for model development, rule logic proposals, and threshold calibration insights.
• Partner with the Detection Team to provide validation support for new detection strategies.
• Develop defensible documentation of methodologies, findings, risk quantification logic and maintain structured playbooks.
• Ensure analytical outputs meet enterprise risk governance standards

Qualifications:

• Bachelor’s Degree required in statistics, mathematics, physics, economics, or other analytical or quantitative discipline.
• 3+ years experience in data analytics, fraud analytics, risk analytics, or financial crime analysis.
• Ability to translate data insights into risk strategy recommendations.
• Extensive experience working with Big Data environment with hands on coding experience within various traditional (SAS, SQL, etc.) and/or open source (i.e. Python, Impala, Hive, etc.) tools.
• Traditional and advanced machine learning techniques and algorithms, such as Logistic Regression, Gradient Boosting, Random Forests, etc.
• Data visualization tools, such as Tableau.
• Excellent quantitative and analytic skills; ability to derive patterns, trends and insights, and perform risk/reward trade-off analysis.
• Ability to build effective presentations to communicate analytical findings to a wide array of audiences.
• Merchant risk or onboarding fraud analytics.
• Knowledge of fraud typologies such as account takeover, promotion exploitation, synthetic identities, and digital ecosystem abuse.
• Analytic rigor and intellectual curiosity.
• Pattern recognition across fragmented data sets.
• Strong written and verbal executive communication skills.
• Effective cross-functional project, resource, and stakeholder engagement and management, with ability to effectively drive collaboration across teams.

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In addition to salary, Citi’s offerings may also include, for eligible employees, discretionary and formulaic incentive and retention awards. Citi offers competitive employee benefits, including: medical, dental & vision coverage; 401(k); life, accident, and disability insurance; and wellness programs. Citi also offers paid time off packages, including planned time off (vacation), unplanned time off (sick leave), and paid holidays. For additional information regarding Citi employee benefits, please visit citibenefits.com. Available offerings may vary by jurisdiction, job level, and date of hire.

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Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law.

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