Data Analyst - Risk Analyst | 3-7 yrs | Mumbai | WFO

Opportunity to shape transformation in a modern banking setupFast-growing, digitally driven bank with strong customer focus About Our Client Our client is a large organization in the financial services industry, specializing in retail banking and loans. They are committed to delivering innovative solutions and maintaining a strong focus on data analytics to support strategic business objectives. Job Description * Design and deploy statistical models including but not limited to Application and Behavioral scorecards using advanced ML techniques. * Lead end-to-end lifecycle: problem framing data extraction feature engineering model development validation deployment monitoring. * Develop statistically robust models using techniques such as (but not limited to): * Gradient Boosting (XGBoost, LightGBM, CatBoost) * Random Forest, Ensemble methods * Neural Networks (MLP) * Apply rigorous evaluation frameworks (AUC, KS, Gini, Lift, PSI, stability analysis). * Address imbalanced datasets, reject inference, segmentation, and portfolio drift. * Build challenger models and drive continuous performance optimization. * Develop and refine credit underwriting strategies aligned to risk appetite, approval rate targets, and portfolio profitability. * Conduct portfolio analytics and recommend cut-off, limit, and pricing strategies. * Collaborate with Risk, Policy, Product, and Tech teams to translate business requirements into deployable decisioning frameworks. * Ensure robust monitoring, back-testing, and periodic recalibration. The Successful Applicant A successful Data Analyst - Risk Analyst should have: * 3-6 years of experience in Credit Risk Analytics * Strong foundation in statistics, hypothesis testing, sampling theory, and classification methodologies. * Proven experience in ML-based credit modeling, model governance and monitoring * Expertise in handling large structured financial datasets. * Proficiency in Python, PySpark, Scikit-learn, and boosting frameworks. * Experience building scalable training pipelines and supporting production deployment. What's on Offer A competitive salary packageOpportunities for professional growth and development in the analytics field.Comprehensive benefits and supportive company culture.Chance to work with a large organization in the financial services industry. If you are a skilled Data Analyst - Risk Analyst looking to make an impact in a dynamic environment in Bandra (East), Mumbai, we encourage you to apply Opportunity to shape transformation in a modern banking setupFast-growing, digitally driven bank with strong customer focus About Our Client Our client is a large organization in the financial services industry, specializing in retail banking and loans. They are committed to delivering innovative solutions and maintaining a strong focus on data analytics to support strategic business objectives. Job Description * Design and deploy statistical models including but not limited to Application and Behavioral scorecards using advanced ML techniques. * Lead end-to-end lifecycle: problem framing data extraction feature engineering model development validation deployment monitoring. * Develop statistically robust models using techniques such as (but not limited to): * Gradient Boosting (XGBoost, LightGBM, CatBoost) * Random Forest, Ensemble methods * Neural Networks (MLP) * Apply rigorous evaluation frameworks (AUC, KS, Gini, Lift, PSI, stability analysis). * Address imbalanced datasets, reject inference, segmentation, and portfolio drift. * Build challenger models and drive continuous performance optimization. * Develop and refine credit underwriting strategies aligned to risk appetite, approval rate targets, and portfolio profitability. * Conduct portfolio analytics and recommend cut-off, limit, and pricing strategies. * Collaborate with Risk, Policy, Product, and Tech teams to translate business requirements into deployable decisioning frameworks. * Ensure robust monitoring, back-testing, and periodic recalibration. The Successful Applicant A successful Data Analyst - Risk Analyst should have: * 3-6 years of experience in Credit Risk Analytics * Strong foundation in statistics, hypothesis testing, sampling theory, and classification methodologies. * Proven experience in ML-based credit modeling, model governance and monitoring * Expertise in handling large structured financial datasets. * Proficiency in Python, PySpark, Scikit-learn, and boosting frameworks. * Experience building scalable training pipelines and supporting production deployment. What's on Offer A competitive salary packageOpportunities for professional growth and development in the analytics field.Comprehensive benefits and supportive company culture.Chance to work with a large organization in the financial services industry. If you are a skilled Data Analyst - Risk Analyst looking to make an im