The Business Analytics Sr Analyst is a member of the Fusion Alerting Strategy Team. This team will be tasked with creating strategies to detect anomalous trends across all LOB’s utilizing statistical and advanced analytical techniques.

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.

Job Skills/Qualifications

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.

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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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Anticipated Posting Close Date:

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Qualified applicants will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.

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