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Strong Tier-1 brand, metro Bengaluru, mid-level generalist analytics role with common skills drives high competition.
Core analytics skills transferable, but fraud domain knowledge raises moderate industry specificity.
Mandatory Python plus explicit 2+ years and SQL/SAS requirements enforce strict shortlisting.
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Manage and execute fraud analytics and strategies for Citi’s North American Retail Bank business focusing on various fraud types including application fraud, synthetic ID fraud, and account takeover.
Own and manage fraud rules, scoring models, and detection strategies leveraging customer and transactional data to identify emerging fraud trends and enhancement opportunities.
Collaborate with senior stakeholders and cross-functional teams to recommend and implement fraud mitigation strategies and generate regular/ad-hoc analytics and reports for monitoring fraud trends.
Bachelor’s degree in Statistics, Economics, Finance, Mathematics, Engineering, or related quantitative field; MBA from a premier institute considered.
Minimum 2+ years of hands-on analytical experience including proficiency in SAS/SQL and mandatory Python experience.
Experience with data visualization tools such as Tableau required.
Experience in fraud strategy/processes or fraud analytics is desired but not mandatory.
Experienced in applying quantitative analytics to fraud detection across multiple fraud types and capable of managing end-to-end fraud strategy execution.
Strong at stakeholder management and cross-functional collaboration in a dynamic, fast-paced environment requiring timely strategy delivery and reporting.
Comfortable working with large datasets and multiple analytical tools to drive actionable insights and operational improvements in fraud prevention.