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Tier-1 bank, metro location, and mid-level (4+ years) candidate pool increases competition despite niche skills.
Specialized credit-risk and decisioning platform skills limit cross-industry transferability.
Mandatory 4+ years, required SAS/SQL and credit-risk domain expertise in a regulated banking environment.
Lead or participate in moderately complex credit risk analytics initiatives focusing on unsecured lending products such as Personal Loans.
Develop, validate, and maintain automated SAS-based testing and data validation frameworks for underwriting and credit decisioning strategies, including UAT, regression, and production validation.
Collaborate with cross-functional teams (US and India) to optimize processes, resolve data/modeling issues, and ensure zero defect leakage in risk analytics deliverables.
Minimum 4+ years of experience in credit risk analytics domain, particularly unsecured lending (Personal Loans).
Bachelor's degree in Engineering, Technology, Mathematics, Econometrics, Computer Science, or related field.
Advanced proficiency in SAS and SQL programming with experience in building automated validation frameworks.
Experience with decision management systems (Zoot, FICO DMP, Experian PowerCurve) or equivalent is required.
Experienced individual contributor capable of leading credit risk analytics projects and mentoring junior staff in a regulated financial services environment.
Strong technical skills in SAS, SQL, and knowledge of data flows, ETL, and risk reporting policies for complex business rule validation.
Familiar with credit underwriting policies, decision strategies, scorecards, and has exposure to cross-border collaboration between US and India teams.