Zonal Manager - Credit

Job description

**Job Purpose** Risk Management is core to Bajaj Finance. - Most of the decisions in Risk Management are data driven and analytical. - Statistical models are required to look at multi-variate dimensions from a risk perspective including calculating the expected credit loss, scenario analysis, forecasting, Stress Testing etc. - Statistical models are built and scorecards are prepared which assesses parameters like PD (probability of default), EAD and LGD which are critical from a regulatory perspective and forms important aspect of regulatory reporting purpose. - This role gives an opportunity of going beyond the above and gives deeper insights on the Regulatory norms on Credit Risk. - The role allows candidate work on areas such as Stress Testing, Expected Credit Loss, Macro Economic stress, Macro stress models/forecasting etc. - Culture Anchor:Think like an Entrepreneur - Encourages new ideas, helps teams improve, and supports them in taking up challengesPractice Emotional Intelligence - Listens to others, stays calm under pressure, and treats everyone with respect. - Transform Continuously - Explores opportunities and encourages teams to improve processes and systems for better delivery. - Own it - Ensures teams achieve targets, drives capability building and inculcates a sense of accountability in the team. **Duties and Responsibilities** ˜Build Stress Testing Framework and execute the same˜Develop, validate, and execute Stress Testing Tools and Stress Testing Engine˜Build, monitor, validate and track PD, LGD, EAD models for Stress Testing as per RBI guidelines ˜Provide analytical solutions through statistical modeling, credit policy and strategy, reporting and data analysis for the BFL businesses˜Support any adhoc deep dive data analysis on portfolio metrices ˜Support in Data analysis and segmentations. - ˜Ongoing liaising with IT, Credit and BIU teams to ensure all policies, processes, data flow are working efficiently, and all required changes are build and implemented suitably **Required Qualifications and Experience** Qualifications- B-Tech/MBA Finance / Postgraduate with 1-3 years in quantitative subjects (Statistics/Data Science)Work Experience - 6-8 years relevant analytical experience in Model development, ML modelling, Forecasting, Segmentation and Clustering. - Preferred Coding languages: SAS, SQL, R, Python. - Classical statistical techniques: Regression, Logistic regression, Clustering, Dimensionality reduction techniques, Hypothesis testing. - Experience in handling huge data base and the ability to do root cause analysis. - Individual contributor with the capability to deliver projects within timeline - Effective verbal and written communication skills