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Tier-1 bank, mid-level analytics role with broad skillset and likely metro hiring drives high competition.
Requires credit-card risk analytics expertise and domain knowledge, limiting cross-industry transferability.
Explicit 5+ years, credit-card domain expertise, and mandatory SAS/SQL/Tableau skills required.
Lead and manage complex risk analytics initiatives across credit card lifecycle processes including originations, collections, recoveries, and delinquency.
Oversee development, deployment, and monitoring of predictive risk models, pilot programs, and stress testing with cross-functional impact.
Make strategic decisions on credit product risk and compliance, mentor teams, and provide actionable insights for senior management reporting.
Minimum 5+ years of progressive Risk Analytics experience, especially in credit card domain focusing on Recovery Strategy analytics and credit risk modeling.
Bachelor's degree in quantitative fields such as applied mathematics, statistics, engineering, finance, economics, econometrics, or computer science.
Proficiency in programming/statistical tools: SAS, SQL, Excel VBA, Macros, Python, R, Tableau, SAS Visual Analytics; familiarity with data management in Oracle/Teradata.
Strong understanding of credit risk domain including P&L and risk drivers; knowledge of advanced statistical and machine learning techniques.
Experienced leader managing large-scale credit risk analytics projects with ability to work cross-functionally and influence business strategy.
Strong technical expertise in credit risk modeling, forecasting, data architecture, and use of advanced analytics for risk monitoring and reporting.
Capable of translating complex analytical findings into executable business strategies under dynamic, compliance-driven environments.