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Tier-1 brand and metro Hyderabad increase competition, but niche credit-modeling specialization limits applicant density.
Requires consumer-lending model experience and regulatory/model governance knowledge, limiting cross-industry transferability.
Explicit 5+/7+ consumer-lending model experience plus mandatory ML and SAS/Python skills enforce strict filters.
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Manage the lifecycle of acquisition credit models including development, evaluation, validation, monitoring, implementation testing, and documentation.
Lead end-to-end annual model review and periodic revalidation activities, serving as the single point of contact for assessments by the Risk Management team.
Drive automation projects for data reporting and extraction using SAS, Python, Pyspark, Tableau and collaborate with stakeholders on multiple projects including providing analytic support for key business initiatives.
Bachelor's degree in quantitative field (Risk, Economics, Finance, Mathematics, Statistics, Engineering) with minimum 5+ years analytical/quantitative experience in consumer lending or 7+ years relevant experience without degree.
Work Experience Required: Minimum 5+ years in analytical/quantitative role related to consumer lending.
Mandatory skills: SAS, SQL, Python/Pyspark, Tableau, knowledge of Machine Learning techniques such as Logistic Regression, Random Forest, XGBoost.
Work Timings: Must be available 06:00 AM to 11:30 AM Eastern Time for meetings; flexibility in remaining hours; occasional travel to regional hubs may be required.
Experienced in full lifecycle credit risk model development and independent model governance in consumer lending domain.
Skilled in combining technical abilities (modeling, programming, automation) with stakeholder collaboration and communication across teams in US and India.
Familiar with credit bureau data, US model governance practices, and able to lead junior team members on analytics activities.