CCAR/PPNR Modelling Role - BFS

CCAR / PPNR Modelling positions open across levels, designation and salary will be decided upon interviewing the candidates and their experience level

To qualify for the role you must have

- A bachelor's degree and approximately 3 years of related work experience; or a master's degree and approximately 2 years of related work experience

- A degree in engineering, Statistics or Econometrics or a related discipline; an M.Stat is preferred

- 2- 8 years of relevant work experience

- Experience of working in the credit risk/credit/ERM domain

Your key responsibilities

- Participate in large scale client engagements

- Consistently deliver quality client services

- Drive high-quality work products within expected timeframes and on budget

- Monitor progress, manage risk and ensure key stakeholders are kept informed about progress and expected outcomes

- Stay abreast of current business and industry trends relevant to the client's business

- Identify new business opportunities

- Understand the firm and its service lines and actively assess/present ways to serve clients

- Develop and maintain long-term client relationships and networks

- Develop relationships with team members across all the firms- practices to serve client needs

- Advise clients on a number of credit risk and capital related topics. 

These areas include:

- CCAR / PPNR modelling

- Regression modelling.

- Model Validation

Skills and attributes for success

Strong experience of statistical modeling in at least one of the following tools/languages is preferable

SAS Base/EG/E-miner

R/S-Plus

Matlab

SPSS

Python

- Strong Excel/VBA skills is a must.

- Ability to explain complex frameworks/statistical models to senior management.

- In addition to core competencies in credit risk measurement and management, a thorough understanding of some or all of the following would be an asset:

- Credit lifecycle within a commercial bank

- Credit risk management infrastructures

- Economic capital and RAPM

- Integration of economic capital into performance measurement frameworks (e.g. Risk Adjusted Return on Capital (RAROC), Shareholder Value Added (SVA)

- Credit Monitoring/Early Warning/Signal System

- Credit Risk Stress Testing

- Credit Risk Reporting/Analytics

- Enterprise Risk Management

- Experience of development/validation of models using machine learning techniques

- Experience of working on digital banking initiatives at Banks