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Strong employer brand and mid-level generalist analytics role increase applicant competitiveness.
Credit risk domain-specific knowledge and lending lifecycle experience limit cross-industry transferability.
Explicit years, mandatory credit-risk experience, SAS/SQL requirement and regulated banking context increase screening rigor.
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Support Risk Business and Development teams by validating business rules and strategies through functional, user acceptance, and regression testing.
Provide analytics to improve efficiency and effectiveness within credit risk analytics for credit card and loan products.
Collaborate with US and India teams to optimize processes with zero defect leakage and support new product launches and BAU releases related to unsecured lending decision engines.
At least 2 years of experience in risk analytics, specifically in credit risk analytics for unsecured lending (credit cards, personal loans).
Bachelor's degree in Engineering, Technology, Mathematics, Econometrics, Computer Science, or related fields.
Proficient with SAS and SQL for data analysis, validation, and testing.
Experience with decision engines (Zoot Webrule Builder, FICO DMP, Experian PowerCurve) and testing methodologies (Unit, SIT, UAT, Regression).
Experienced in end-to-end strategy implementation and validation across unsecured lending lifecycle (Acquisition, Portfolio, Collections).
Skilled in managing UAT and production deployments including post-production monitoring and issue resolution.
Technical expertise in automation tools/scripts (VB Script, Selenium/UFT, UNIX Shell scripting) and familiarity with Agile development processes.