Experience : 5-10 years in Banking Industry(retail & non-retail)
Technical Skillset :
Skilled in : SAS/SQL/R/Python
- Advanced skills in MS Excel
- Predictive Modeling/Logistic / Linear Regression
- Decision Trees
Banking Domain Requirements :
- Strong understanding of banking products such as mortgages, credit cards, loans and advances
- High level of proficiency in the development of predictive risk models and statistical techniques such as logistic regression, clustering, segmentation etc.
- Hands-on experience working on PD, EAD, LGD models, RWA calculations, Capital computations
- Experience working with leading global banks on the regulatory model development either for Secured or Unsecured portfolios
- Self-driven, able to work independently, strong problem-solving skills along with excellent communication
Role Competencies :
- Experienced in the development of credit risk models for BASEL reporting, PD, LGD, EAD and/ stress testing or should be well versed with the understanding of these concepts
- Skilled in validation and monitoring of internal and external risk models by computing standard metrics
- Skilled in developing and analyzing product-specific solutions within the banking domain varying across underwriting/monitoring loan portfolios, developing collections scorecards, loss forecasting amongst others
- Ability to work with key stakeholders across businesses, client portfolio teams to derive insights and calibrate model performance
- Ability to present the findings of the analysis to stakeholders and hold presentations for a larger audience
- Ability to drive discussions with the stakeholders and present the findings/summary of the project activities
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