Smith Hanley Associates
Location: Pittsburgh, PA
Salary: $95,000 – $130,000 depending on experience
Contact: Sean Murphy – firstname.lastname@example.org
Large Financial Institution is seeking a Quantitative Analyst in the commercial credit risk model development group within the quantitative modeling center of excellence. This position will provide analytical support in the development, implementation, monitoring and maintenance of Basel II compliant quantitative risk measurement models such as PD, LGD and EAD for the wholesale portfolios in the bank. This position will also support the stress testing related activities for the bank. The individual will develop and enhance Commercial Credit Risk Models including Probability of Default (PD), Loss Given Default(LGD), Exposure at Default (EAD) and custom credit quality indices to forecast future credit quality trends and credit limits. Furthermore, the successful candidate will work with Commercial Lines of Business in understanding portfolio and default prediction challenges and issues to develop business friendly solutions as well as maintain open channels of communication with the internal Model Risk Management group, auditors, regulators and other key business partners.
Desired Skills and Experience
” 4 – 9+ years experience in modeling or quantitative analytics in financial services with a bachelor’s degree in a quantitative discipline will be considered in lieu of an advanced degree and/or PhD or M.S. in quantitative discipline (e.g., statistics, economics, mathematics, financial engineering, etc.), or an MBA Finance with quantitative background is required. ” MUST HAVE AT LEAST 3 YEARS OF ACTUAL PROFESSIONAL EXPERIENCE IN MODELING/CREDIT RISK OUTSIDE OF ACADEMIA TO BE CONSIDERED. ” Project management and multitasking capabilities with the ability to meet strict deadlines ” Work well within a team environment and build positive relationship with other staff and management ” Prior experience in the financial services industry is preferred ” Ability to use advanced statistical programming languages (e.g., SAS, S+, R, Matlab, etc.) and database management is required. ” Excellent communication and presentation skills and ability to work closely with cross-functional teams ” Knowledge of financial products including loans, bonds, derivatives etc. is preferred ” Ideal candidate should have the practical skills to translate mathematical concepts to business users. ” A demonstrated ability in application of commonly used statistical techniques like linear regression, logistic regression, decision trees etc is needed.