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Mid-level, metro ML role with common skills at a recognizable financial brand.
Credit models require consumer-lending domain knowledge and governance, limiting cross-industry transferability.
Explicit 5+/7+ years, domain-specific credit modeling and mandatory tech stack make filters stringent.
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Manage the full lifecycle of Acquisition Credit models, including development, evaluation, validation, monitoring, implementation testing, and documentation.
Serve as the single point of contact for model assessments by the Risk Management team and lead annual model reviews and revalidation activities.
Lead automation projects using SAS, Python, Pyspark, Tableau and provide analytic support on key business initiatives while mentoring junior team members.
Bachelor's degree in quantitative field (Risk, Economics, Finance, Mathematics, Statistics, Engineering) with minimum 5+ years related analytical/quantitative experience in consumer lending, OR 7+ years experience without degree.
Proficiency in SAS, SQL, Python/Pyspark and reporting tools like Tableau.
Experience with statistical and machine learning techniques such as Logistic Regression, Random Forest, XGBoost.
Work timings 2:00 PM to 11:00 PM IST, with required availability aligned to 06:00 AM - 11:30 AM US Eastern Time for meetings.
Experienced in consumer lending credit model development and governance, preferably familiar with US Model Governance standards.
Strong technical skills in credit risk modelling, data analysis, and automation with ability to communicate complex insights clearly.
Capable of independently managing multiple projects and leading junior team members in a collaborative global environment.