Credit Suisse - ENO - CRM - Credit Risk Quants - IIT

We offer :

CRM - Credit Analytics Mumbai - Job Description

For the IB International Risk Models & IB Rating Models Team (India Quant Team)

Role

The CRM-Credit Analytics at Credit Suisse is responsible for the methodology, measurement and reporting of credit risk. Credit Suisse has an industry-leading Economic Capital framework and uses the Advanced IRB approach under Basel to calculate regulatory capital requirements related to risks in banking and trading books. These approaches to economic and regulatory capital for credit risk require Credit Analytics to estimate appropriate probability of default (PD), loss given default (LGD) and credit conversion factors (CCF) for all our exposures.

Credit Suisse is seeking a Quantitative Credit Risk Analyst to assist in the development of obligor and transaction level credit risk models and the estimation of credit risk parameters (PD, LGD, CCF) for use in regulatory and economic capital calculations. We are seeking a quantitative analyst with excellent technical skills and ideally some prior experience of quantitative credit risk modeling and knowledge of Basel regulations.

Main Duties and Responsibilities

- Development of credit risk PD rating models at single obligor and transaction level.

- Annual review of rating models which involves performing core technical modeling and liaising with independent validation teams and across the risk and finance functions.

- Assisting in the preparation of regulatory (e.g. Pillar III) disclosures relating to Basel II.

- Participating in project work around improvements to credit risk parameters.

- Performing ad-hoc analysis.

- Participating in our regular dialogue with our supervisors where appropriate.

- Writing and maintaining detailed technical documentation and preparing presentations for senior management and bank supervisors.

You Offer :

- Strong technical skills with some knowledge of credit risk modeling, economic capital and Basel regulatory capital, and ideally significant relevant experience gained in a banking, consultancy or regulatory environment

- Master's degree or PhD in numerical discipline or an advanced degree from top tier university. Exceptional candidates from other streams with keen interest and relevant skills will also be considered. However knowledge and affinity towards basic statistical techniques and formal concepts is essential

- Strong interest in working with mathematical and statistical techniques and good background knowledge of quantitative finance

- Knowledge of statistical and mathematical software packages (e.g. R, Stata, Matlab, etc.) and programming languages (VBA, C++, SQL, etc.)

- Ability to communicate well both informally and formally, including writing extended documentation