I am currently working with a client looking for a VP-level candidate who will be responsible for developing methodologies and managing analytics of credit risk ratings modeling for the Wholesale portfolio. Candidates should have an advanced quantitative degree along with 7+ years of experience in credit risk quantitative modeling with strong experience in credit risk rating model development and proficiency in Python.
Responsibilities:
- Develop credit risk rating model, test, implement and deliver the comprehensive technical and non-technical model documentation.
- Obtain and prepare model development data in support of standing up credit risk rating models.
- Select the champion modeling methodology after evaluating multiple options
- Perform quantitative research to implement model changes, enhancements and remediation plans.
- Work with stakeholders across business and functional teams during model development and implementation process.
- Create tools and dashboards which can enhance and improve the risk analysis.
- Conduct analysis of the implemented model short-comings and design model enhancement plans.
Qualifications:
- Master's Degree in quantitative subject; (PhD preferred)
- 7+ years of experience in credit risk quantitative modeling with strong experience in credit risk rating model development.
- Strong knowledge and experience in statistics and statistical tools (statistical hypothesis and discriminatory power testing, optimal binning, all types of regressions with optimal variable selection, time series models, Bayesian statistics, MCMC, state space model and etc.)
- Proficient programming skills in python (other languages such as R, SQL is a plus)
- Experience in the use of machine learning techniques applied to risk modeling is a plus
