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Tier-1 brand, metro location, generalist analytics role with common Python/SQL skills increases applicant competition.
Core analytics skills are transferable, but fraud domain knowledge increases industry specificity.
Mandatory Python/SAS/SQL skills and explicit 2+ years make shortlisting relatively strict.
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Manage and execute fraud analytics and strategies for Citi's North American Retail Bank, focusing on fraud lifecycle including application fraud, synthetic ID fraud, and account takeover.
Own fraud rules, scores, and detection strategies by analyzing customer and transactional data to identify emerging fraud trends and develop mitigation strategies.
Collaborate with senior stakeholders and cross-functional teams to recommend and implement fraud prevention strategies and produce regular reporting and dashboards for fraud monitoring.
Bachelor’s degree in Statistics, Economics, Finance, Mathematics, Engineering, or related quantitative field.
Minimum 2+ years of hands-on analytical experience.
Mandatory hands-on proficiency in SAS, SQL, and Python; experience with data visualization tools like Tableau.
Experience in fraud strategy/processes and/or fraud analytics is desired but not mandatory.
Experienced in applying data analytics to identify and mitigate complex fraud patterns within financial services or similar sectors.
Skilled at managing fraud detection strategies and working closely with senior stakeholders and cross-functional teams.
Capable of delivering insights and actionable strategies in a fast-paced, dynamic environment using advanced analytical and visualization tools.