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Tier-1 bank and metro location but niche credit strategy reduces generalist applicant density.
Requires specialist retail/auto credit decisioning experience, limiting cross-industry transferability.
Explicit 4–7 years, mandatory domain experience, and required Python/SQL make shortlisting stringent.
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Analyze consumer and dealer credit performance to identify approval rate, booked volume, loss rate, and profitability drivers and recommend strategy.
Develop, refine, and maintain credit decisioning strategies balancing risk, growth, and P&L trade-offs.
Lead test-and-learn strategies, support credit policy execution, monitor portfolio risks, and collaborate cross-functionally to implement strategy changes and track portfolio outcomes.
4–7 years experience in retail or auto credit decisioning, underwriting, or credit policy execution in banking, fintech, or credit analytics.
Proficiency in Python and SQL for data extraction and basic analytics.
Strong understanding of consumer credit risk and credit portfolio outcomes.
Experience communicating effectively with US-based stakeholders across time zones.
Experienced in decisioning engines or rules-based platforms with exposure to rule governance and policy operationalization.
Skilled in running challenger rule tests and structured experimentation frameworks.
Familiar with portfolio monitoring techniques like vintage/cohort analysis and early delinquency indicators, ideally with fintech or banking background and strong stakeholder management skills.