AVP - Analytics/Credit Risk Data - SAS + Regulatory Modelling - Banking Domain

AVP - Analytics/Credit Risk - SAS + Regulatory Modelling - Banking Domain

Experience - 5-10 years in banking industry(retail&non retail)

Technical skillset:

Skilled in:

- SAS

- SQL

- R or Python

- Advanced skill in MS-Excel

- Predictive Modelling

- Logistic /Linear Regression

- Decision tress

Banking Domain Requirements:

- Strong understanding of banking projects such as mortgages, credit cards, loans and advances.

- High level of proficiency in development of predictive risk model and statistical techniques such as logistics 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 on unsecured portfolios

- Self driven,able to work independently ,strong problem solving skills along with excellent communications.

Role Competencies:

- Experience in development of credit risk models for BASEL reporting PD, LGD, EAD and/stress testing or should be well versed with understanding of theses concepts

- Skilled in Validation and monitoring of internal and external risk models by computing standards metrics.

- Skilled in developing and analysing product specific solution when banking domain vary across understanding /monitoring loan portfolios ,developing collection scorecards , loss forecasting amongst others

- Ability to work with the key stakeholders across businesses, client portfolio team to derive insights and calibrate model performance.

- Ability to present finding of the analysis to stakeholders and hold presentation for the larger audience.

- Ability to drive discussion with the stakeholders and present the findings/summary of the project activities.