About Global Consumer Bank
Citi’s Global Consumer Bank (GCB), a global leader in credit cards, wealth management and commercial banking, serves as a trusted partner to more than 110 million customers in 19 countries worldwide, providing financial services that enable growth and economic progress. The Global Consumer Bank operates four business lines — Branded Cards, Retail Services, Retail Banking and Commercial Banking — in three priority markets: Asia, Mexico and the U.S. Over the past few years, our business has transformed to become a simpler, leaner, focused franchise.
Citi is on a journey to become a world-class digital bank has tangibly accelerated with a mobile-first strategic focus and deployment of a new, agile operating model fostered massive improvements in the design and delivery of digital features and in the customer experience. As a result the franchise has seen significant growth in the number of digital users, mobile downloads and digital engagement.
About the GCB Fraud Prevention Organization
The financial crimes environment continues to be challenging, with cybercrime worldwide remaining highly lucrative and criminals becoming more organized and sophisticated, making it harder to distinguish between real and fraudulent customers. To combat the agile threat, the Global Consumer Bank (GCB) Fraud Prevention organization operates leveraging an intelligence-led, threat driven model that targets fraud along the entire fraud lifecycle, enabling the integration of analysis, dissemination of information and coordination of action with speed and agility across businesses and regions.
This role will be tasked with creating strategies/rules to detect anomalous trends across all LOB’s utilizing statistical and advanced data science techniques.
Role & Responsibilities:
The Business Analytics Lead Analyst is a member of the Fusion Alerting Strategy Team. This team will be tasked with creating strategies/rules to detect anomalous trends across all LOB’s utilizing statistical and advanced data science/ML techniques.
Key responsibilities include:
- This role will be tasked with creating strategies/rules to detect anomalous trends across all LOB’s utilizing statistical and 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.
- Lead and recommend process/logic change to drive efficiency and enhance customer experience.
- Provide actionable insights to senior global stakeholders by leveraging data analytics and reporting.
- Ability to mentor and train junior team members.
- 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 Global 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 or Python(Preferred).
- Prior experience in developing dynamic dashboards using visualization tools such as Tableau.
- Model development in any risk domain will be preferable.
- 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.