Citi Group AVP Fraud Fusion Business Analytics Sr Analyst 

United States, Texas, San Antonio 

198066265

Key responsibilities include:

• This role will be tasked with creating strategies/rules to detect anomalous trends across all LOB’s utilizing statistical/advanced data science techniques.
• Analysis of customer data and transactional data to identify emerging fraud trends, develop, and improve fraud strategies.
• Periodic review and development of dashboards and communication of fraud results internally and to the business using advanced visualization techniques.
• Perform gap analysis to identify system weaknesses and mitigating measures.
• Continuously improve processes and strategies by exploring and evaluating new data sources, tools, and capabilities.
• Recommend process/logic change to drive efficiency.
• Provide actionable insights to senior global stakeholders by leveraging data analytics and reporting.
• Focus on development of tactical and strategic MIS dashboards with high visibility for key stakeholders.
• Drive the end-to-end testing approach – including test case documentation, review and monitoring of rule performance, fine-tune rules – and strategy implementation.
• Partner with a variety of cross-functional teams such as Fraud Policy, Analytics & Modeling, and Security Operations Center (SOC) to design effective strategies to detect Fraud.
• Partner with the Fraud Analytics Data Science function to increase sophistication of anomaly detection analytics and develop new detection models and analytical solutions.

Education & Experience:

• Bachelor’s degree in Engineering, Statistics, Economics, Finance, Mathematics or a related quantitative field from a premier institute required. (Master's degree not required but beneficial)
• Minimum 5+ relevant experience in data analysis, data mining, or statistical analysis.
• Must have a working knowledge of SQL, Teradata, RDBMS, Hadoop/Hive Tools.
• Experience in statistical analysis with working knowledge of at least one of the following statistical software packages: SAS/R/ Python.
• Experience with a prior focus in financial services analytics.
• Prior experience in developing dynamic dashboards using visualization tools such as Tableau.
• Data Science work in any risk domain will be good to have.
• Experience in identifying fraud patterns in large consumer banking portfolios.
• Successful candidate will have a demonstrable analytic, problem solving, and leadership skills, and has the ability to deliver projects in a fast-paced environment.
• Excellent quantitative and analytic skills and data-driven mindset; ability to derive patterns, trends and insights, and perform risk/reward trade-off;
• Ability to effectively collaborate with cross-functional partners and management.
• Solutions-oriented “can do” attitude, with ability to drive innovation via thought leadership while maintaining end-to-end view.
• Extremely detail-oriented, with strong, intellectual curiosity. Ability to effectively multi-task and work in a fast-paced and evolving environment, while setting meeting high standards.

Anticipated Posting Close Date:

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