Program Lead - Scorecard Development

As a Credit Risk Model Developer at Tiger Analytics, you will be a key player in the end-to-end development, implementation, and monitoring of application and behavioral scorecards within the dynamic retail banking division, focusing primarily on the unsecured lending portfolio in the Indian banking context. Your expertise and contributions will be instrumental in enhancing credit risk management capabilities, optimizing lending decisions, and driving profitable growth through advanced analytical techniques and robust statistical models. Your responsibilities will include leading the design, development, and validation of new application and behavioral scorecards tailored for the Indian retail banking landscape, with a specific focus on personal loans, credit cards, and other unsecured portfolios. You will utilize advanced statistical methodologies and machine learning techniques, leveraging Python for data manipulation, model building, and validation. Additionally, you will ensure robust model validation, back-testing, stress testing, and scenario analysis to ensure model robustness and stability while adhering to regulatory guidelines and internal governance. Furthermore, you will drive the deployment of developed scorecards into production environments on AWS, collaborating with engineering teams to integrate models into credit origination and decisioning systems. You will also implement and manage MLOps practices for continuous model monitoring, re-training, and version control within the AWS ecosystem. In terms of data strategy and feature engineering, you will proactively identify, source, and analyze diverse datasets to derive highly predictive features for scorecard development. Addressing data quality challenges and ensuring data integrity and suitability for model inputs will also be a key part of your role. Your role will also involve establishing and maintaining comprehensive model performance monitoring frameworks, tracking key performance indicators like Gini coefficient, KS statistic, and portfolio vintage analysis. Based on performance degradation, regulatory changes, or evolving market dynamics, you will identify triggers for model recalibration or redevelopment. The ideal candidate for this role will have 3-10 years of hands-on experience in credit risk model development, with a strong focus on application scorecard development and exposure to behavioral scorecards within the Indian banking sector. A Bachelor's or Master's degree in a quantitative discipline and exceptional hands-on expertise in Python, proficiency in SQL, and familiarity with AWS services relevant to data science and machine learning are essential requirements. Strong analytical, problem-solving, and communication skills are also crucial for effectively communicating complex technical concepts to both technical and non-technical stakeholders.,