CAIA's Career Center is an easy-to-use, comprehensive resource connecting job seekers with employers in the growing AI field. Use your knowledge and credibility to advance your career or build a talented team for your organization. Opportunities targeted to CAIA Charterholders are prioritized.
In order to search for jobs specifically for CAIA Charterholders or those pursuing the CAIA Charter please enter “CAIA” in the search panel.
This will enable you to search for CAIA specific roles globally.
Capital Stress Testing (CCAR) Market Risk Modeler # 101626
Credit Suisse -
December 23, 2017
New York, New York
We Offer The Market Risk Modeler is a role within the CCAR program, working under the Head of the Challenger Team. The primary responsibilities include developing CCAR Challenger models, overseeing junior modelers, and collaborating with any vendors supplying inputs in the development of Credit Suisse's models. This model development role encompasses the modelers' role throughout the entire model lifecycle, and includes, but is not limited to:
You will work with market risk managers, market risk model developers, front office valuation modelers, CCAR model developers, and the Lines of Business, to define the modeling scope, and to identify challenger or benchmark model requirements
You will formulate, estimate, test and implement models
You will assess the reasonableness of CCAR Champion results by using Challenger models, examining the impacts of modeling issues in the Champion models, or in their underlying assumptions
You will socialize Challenger models and results with functional model owners and all other critical stakeholders
You will write technical model methodology documentation, as well as analytical assessment documents
You will interact with Model Risk Management during model validation
You will assist in any BRDs (Business Requirement Documents) needed to meet implementation requirements
You will participate in review and challenge sessions
You will assist in functional model owners, as well as Model Risk Management, in ongoing model performance monitoring and review
You will lead or working with modelers to maintain and redevelop CCAR Challenger models as necessary
Role & Responsibilities
You will develop methods and tools to assess the reasonableness of CCAR Champion model results
You will document model methodology and related processes, as well as assessments of Champion model results
You will develop tools to facilitate testing, as well as ongoing performance monitoring of models
You will develop and execute ongoing maintenance of CCAR models for instantaneous loss (i.e. trading mark-to-market loss, trading issuer default loss, counterparty default loss, credit valuation default loss) and 9Q market risk RWA projections (i.e. VaR/SVaR, Standardized Specific Market Risk (SSMR), and the Simple Supervisory Formula Approach (SSFA) for securitized products)
You will supervise internal teams of junior modelers to ensure that standards for projections model development are met
You will collaborate with internal and external teams responsible for oversight, development, implementation, and review of projections models
You will Liaise with CSH USA's independent model review and validation function, and address any required remediation
Credit Suisse maintains a Working Flexibility Policy, subject to the terms as set forth in the Credit Suisse United States Employment Handbook.
You have at least four years of risk management, valuation or risk model development, econometric modelling or risk analysis experience within the financial industry, preferably with prior CCAR / stress-testing experience. Key skills include risk management, risk modeling, econometric time-series modelling, financial forecasting, or Monte Carlo simulation.
You have a Master's degree in a quantitative discipline (Economics, Mathematics, Engineering, Statistics, Physics, etc.). A PhD in these disciplines would be a valuable plus.
You have advanced proficiency in R, Excel, and VBA. Additional experience with similar tools, such as Matlab, SAS, Stata, and SPSS would be beneficial.
You have excellent written skills, ability to compose well-structured technical model methodology documentation.
You have excellent verbal communication and presentation skills, ability to engage in concise, effective discussions.
You are comfortable implementing models in R, and carrying out tactical software development to interface with existing technology/modeling infrastructure.