Business Analytics Lead Analyst

Bachelor’s degree, or foreign equivalent, in Computer Engineering, Information Systems, Statistics, or related field
5 years of progressive, post-baccalaureate experience as a Software Engineer, Application Development Analyst, Fraud Risk Analyst, Business Analytics Analyst, Business Analytics Manager, or related position
Experience with Base and Advanced SAS programming including constructs like Macros & Proc SQL
Experience with data sources like Fiserv Falcon data files, Broadcom ARCOT Reporting, SQL Server Tables, Teradata, Fiserv First Track data files
Experience with Broadcom ARCOT, DefenseEdge, SAS Fraud Management, Fiserv Trauma Rules, Fiserv Provisioning Plus, Angoss Knowledge Studio Workstation
Experience with data visualization and report generation using SQL, SAS, Excel Pivots, Hive, Impala and Tableau
Knowledge of SQL techniques like Joins, Complex Query, Common Table Expression
Domain Knowledge of Credit Card Fraud Detection, Retail Credit Cards transactional processing, understanding of Financial Systems and Regulatory Knowledge
Problem Solving, Probability and statistics, Exploratory Data Analysis, Feature Engineering, Model Validation, Predictive analytics techniques like decision trees and logistic regression
Experience with report migrations and SDLC (Software Development Life Cycle) methodologies

Manage fraud analytics and execute pertinent strategies in support of Citi’s North American and global credit card businesses
Use SAS Studio and SQL to query and leverage data to identify fraud trends
Design and implement strategies to prevent and mitigate fraud attacks across different areas, including application fraud, account takeover, and other sophisticated new attack schemes
Partner closely with Fraud Policy, Operations, and various other partners to keep apprised of business and technology direction and to determine potential and existing fraud impacts
Use in-depth knowledge of programming languages, including SAS, SQL and Python, to execute the fraud strategies in production environment, which requires coding, testing, implementation, and post-implementation validation
Use domain knowledge to effectively execute the fraud mitigation strategies, build automated reporting and visualizations and conduct complex data analysis
Train and mentor junior team members on critical domain knowledge related to fraud mitigation processes

No preferred qualifications provided.