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Tier-1 brand and metro location increase competition, but niche credit-modeling skills limit applicant density.
Strong consumer-lending and credit bureau expertise required, making cross-industry transfers difficult.
Explicit 5/7+ years requirement, consumer-lending domain experience, plus SAS/Python/PySpark and governance skills.
Manage the full lifecycle of Acquisition Credit models including development, evaluation, validation, monitoring, implementation testing, and documentation.
Lead end-to-end annual model reviews, periodic revalidation, and act as single point of contact for Risk Management assessments.
Drive automation projects (using SAS, Python, Pyspark, Tableau) and provide analytic support on key business initiatives, mentoring junior team members.
Bachelor's degree with quantitative background (Risk, Economics, Finance, Mathematics, Statistics, Engineering) plus 5+ years in analytical/quantitative role in consumer lending, or 7+ years without degree.
Experience with SAS, SQL, Python/Pyspark, and reporting tools like Tableau mandatory.
Knowledge of statistical and machine learning techniques such as logistic regression, Random Forest, XGBoost required.
Work timings: 2:00 PM to 11:00 PM IST with availability aligned to US Eastern Time (06:00 AM - 11:30 AM ET) for meetings.
Experienced in consumer lending credit risk modeling with hands-on knowledge of US model governance and credit card policies.
Strong technical skills in model development lifecycle including data preparation, feature engineering, model evaluation, and automation.
Capable of managing multiple projects independently, collaborating with cross-functional teams, and mentoring junior analysts.