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Tier-1 bank brand, metro Bangalore, mid-level generalist role, and broad SAS/decisioning skills increase applicant competition.
Requires credit-risk and decisioning domain expertise, limiting transferability across unrelated industries.
Explicit 4+ years, mandatory SAS/SQL and domain-specific decisioning skills make filters stringent.
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Lead and participate in risk analytics initiatives focusing on credit risk products, specifically unsecured lending including personal loans.
Develop, perform, and maintain automated validation frameworks and testing scenarios (UAT, regression, production) to ensure business rules, underwriting policies, and decision strategies are correctly implemented with zero defect leakage.
Collaborate with cross-functional teams in US and India for data validation, model documentation, issue resolution, and continuous optimization of risk analytics processes.
4+ years of experience in risk analytics, specifically in credit risk analytics domain.
Bachelor's degree in engineering, Technology, Mathematics, Econometrics, Computer Science, or related field.
Advanced SAS and SQL programming skills with experience in automated data validation and testing framework development.
Experience with decision systems such as Zoot, FICO DMP, or Experian PowerCurve.
Experienced in unsecured lending products (Personal Loans, Credit Cards, Business Loans) with deep understanding of credit underwriting policies and decision strategies.
Proficient in complex data analysis, ETL processes, and validation across structured and unstructured databases (including MongoDB).
Capable of working independently on moderately complex projects and leading or mentoring junior staff, coordinating effectively with multi-geographical teams.