Deputy Area Manager - B2C Underwriting Rural
Deputy Area Manager - B2C Underwriting Rural
Posted on :
13-04-2025
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1 Vacancy
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Job Description
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 multivariate 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.
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
Model build design
Algorithms that should be used in model building
Business interpretation of statistical models
Model Monitoring results and its interpretation
Updated on new statistical modeling methods
Writing efficient SQL and Python queries
Incorporate the regulatory changes as and when announced
Liasing with IT and other teams to get models implemented in the systems
Qualifications
BTech/MBA Finance / Postgraduate with 13 years in quantitative subjects (Statistics/Data Science)
Work Experience
13 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
Required Experience:
Manager
Employment Type
Full-Time
Key Skills
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