Work Timings : 12:30 PM to 9:30 PM Hybrid Work: 3 days' Work from office as of now and may subject to change in future Role Purpose : Manage all the analysts in the Bangalore based team and develop their skills in using various risk management tools and techniques. Assist the department head in maintaining and enhancing productivity of the department. Key Responsibilities : As the second senior-most member of the team, assist the department head in all matters and depute for the department head when required. Develop competencies to assume the department head role at short notice. Design and implement risk management models for consumer lending products. Manage Projects, train and supervise team members in various risk management tools and techniques. Acquire and update knowledge of 1FBSSPLs customer information database and overall business economics. Work on development and deployment of risk management systems and processes. Undertake preparation and upgradation of risk related systems and policies. Preferred candidate profile Key Requirements : Professional with analytics experience preferably in Credit Card Domain . Must have 5 to 6 years hands-on experience in analytical tools like SAS, SQL (advanced) , and advanced excel functions. Experience in R, Python, and BI tools (Tableau, PowerBI, etc.) would be an added advantage. Should have good understanding of statistical concepts specially related to classification, regression, and time-series models. Must have worked on at least one of the following statistical techniques like logistic regression, forecasting, segmentation, etc. Extensive experience in production deployment of MIS reports as well as ad-hoc analysis. Self-driven, ability to work independently, as well as handle a small team. Minimum 8 years of relevant experience. Should have excellent communication skills to interact with senior Bank personnel.
Work Timings : 12:30 PM to 9:30 PM Hybrid Work: 3 days' Work from office as of now and may subject to change in future Role Purpose : Manage all the analysts in the Bangalore based team and develop their skills in using various risk management tools and techniques. Assist the department head in maintaining and enhancing productivity of the department. Key Responsibilities : As the second senior-most member of the team, assist the department head in all matters and depute for the department head when required. Develop competencies to assume the department head role at short notice. Design and implement risk management models for consumer lending products. Manage Projects, train and supervise team members in various risk management tools and techniques. Acquire and update knowledge of 1FBSSPLs customer information database and overall business economics. Work on development and deployment of risk management systems and processes. Undertake preparation and upgradation of risk related systems and policies. Preferred candidate profile Key Requirements : Minimum 8 years of relevant experience. Professional with analytics experience preferably in Credit Card Domain . Must have 5 to 6 years hands-on experience in analytical tools like SAS, SQL (advanced) , and advanced excel functions. Experience in R, Python, and BI tools (Tableau, PowerBI, etc.) would be an added advantage. Should have good understanding of statistical concepts specially related to classification, regression, and time-series models. Must have worked on at least one of the following statistical techniques like logistic regression, forecasting, segmentation, etc. Extensive experience in production deployment of MIS reports as well as ad-hoc analysis. Self-driven, ability to work independently, as well as handle a small team. Should have excellent communication skills to interact with senior Bank personnel.
Work Timings : 12:30 PM to 9:30 PM Hybrid Work: Out of 5 days, 3 days' Work from office as of now and may subject to change in future (Tue-Wed-Thu) Role Purpose : Work towards development and deployment of risk related models, systems and processes. Key Responsibilities : Use risk management tools and models to drive analytics for consumer lending products. Identify portfolio optimization opportunities and provide recommendations to Senior Management. Support the supervisor in all Risk related initiatives. Track actual portfolio performance and credit risk management strategy results. Work on development and deployment of risk management systems and processes. Undertake preparation of risk related systems and policies. Preferred candidate profile Key Requirements : Professional with analytics experience preferably in Credit Card Domain . Must have experience in SQL and advance excel. Experience in MIS reports and ad-hoc analysis Experience in other analytical tools like SAS , R, or Python, would be an added advantage. Exposure to Machine Learning and statistical techniques like logistic regression, clustering, segmentation etc (preferred but not mandatory). Self-driven, ability to work independently, and strong problem solving skills. Minimum 2+ years of relevant experience Should have excellent communication skills to interact with senior Bank personnel.
Work Timings : 12:30 PM to 9:30 PM Hybrid Work: Out of 5 days, 3 days' Work from office as of now and may subject to change in future (Tue-Wed-Thu) Role Purpose : Work towards development and deployment of risk related models, systems and processes. Key Responsibilities : Use risk management tools and models to drive analytics for consumer lending products. Identify portfolio optimization opportunities and provide recommendations to Senior Management. Support the supervisor in all Risk related initiatives. Track actual portfolio performance and credit risk management strategy results. Work on development and deployment of risk management systems and processes. Undertake preparation of risk related systems and policies. Preferred candidate profile Key Requirements : Professional with analytics experience preferably in Credit Card Domain . Must have experience in SQL and advance excel. Experience in MIS reports and ad-hoc analysis Experience in other analytical tools like SAS , R, or Python, would be an added advantage. Exposure to Machine Learning and statistical techniques like logistic regression, clustering, segmentation etc (preferred but not mandatory). Self-driven, ability to work independently, and strong problem solving skills. Minimum 2 to maximum 4 years of relevant experience Should have excellent communication skills to interact with senior Bank personnel.