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Tier-1 brand, generalist analytics title, and Mumbai metro location increase candidate competition.
Strong credit risk modelling and banking domain expertise makes background not easily transferable.
Explicit 8+ years, domain-specific credit risk modelling and mandatory SAS/Python and ML skills make filtering strict.
Build advanced credit risk models leveraging bureau and alternate data for clients, focusing on acquisition and limit assignment strategies.
Deliver high-quality analytical and value-added services within agreed timelines, engaging with business and technical teams to align on proposed solutions.
Use data analysis and customer insights to develop value propositions and support portfolio risk management.
8+ years of experience in credit risk modelling across customer life cycle, preferably with MSME lending domain expertise.
Strong knowledge of machine learning techniques (e.g., Gradient Boost, KNN) and modelling frameworks (Linear Regression, Logistic Regression, Decision Trees).
Proficiency in Python and statistical modeling tools (e.g., SAS), with good applied statistics skills.
Work location: Mumbai; Work Experience Required: 8+ years
Experienced in MSME lending credit risk modelling with understanding of underwriting, credit assessment, risk segmentation, and portfolio risk management.
Skilled in translating technical model outputs into commercial benefits for financial services clients.
Capable of managing large projects and collaborating effectively across business and technical teams in a financial services environment.