
Role Overview:
- Develop and deploy predictive models for credit risk and loan performance.
- Build analytical frameworks for customer segmentation, credit scoring, and underwriting automation.
- Work with microfinance and credit bureau data to improve borrower risk assessment.
Key Responsibilities:
- Analyse rural market dynamics and borrower behaviour to design data-driven lending strategies.
- Collaborate with product and risk teams to design and refine rural and unsecured lending products.
- Develop machine learning pipelines using Python, SQL, and cloud-based analytics platforms.
- Implement and evaluate model performance through validation and monitoring frameworks.
- Work with engineering teams to support model deployment and operationalization.
Requirements:
- Strong experience in Python and SQL for data analysis and model development.
- Hands-on experience in machine learning techniques, including Logistic Regression, Tree-based models, Clustering, and Gradient boosting models.
- Experience working with credit risk or lending analytics in BFSI.
- Familiarity with cloud platforms such as GCP, BigQuery, or similar environments.
- Ability to translate business problems into analytical solutions.
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