Quant Risk Analyst: Credit Risk Modelling, Banking, Boston recruitment
You will be involved in various aspects of the further development and implementation of mathematical models and methods to quantify the credit risk on single derivative transactions, and portfolios of derivatives. In addition, you will perform statistical and econometric modelling of data. In quantifying the credit risk, you will collaborate closely with business users as well as other departments within Risk Management.
The successful candidate will have performed a modelling role (combination of statistics, programming and problem solving skills) in a risk department for up to 3 years post PhD and will be looking to extend and develop their skills and learn from experienced mentors in this domain. The right candidate will have a high level of interest in business and banking and with commercial banks products, operations and credit processes.
A background and knowledge of the Basel rules and regulations is essential and an understanding of compliance and implications of Basel, FDIC, Federal Reserve regulatory frameworks as well as U.S. and International accounting standards would be considered a plus.
You need a strong knowledge of financial, mathematical, and statistical theory and practice, in particular knowledge of option valuation, portfolio theory, stochastic processes and time series analysis.
Experience in developing macroeconomic forecasting models, knowledge of Vector Auto Regression, time series models and cross sectional analysis is desirable. Prior experience in loss forecasting both in retail and wholesale portfolios would be an excellent base on which to build.
If you are suitably qualified and wish to be considered for this or any other role in quantitative risk analytics in the Boston area, please upload your resume for the attention of Ruth Steel and her team at Huxley Associates, Boston.