Work in a dynamic risk analytics team
Develop high level models for a top Investment Bank
About Our Client
The client is a Leading Investment Bank
The incumbent will be responsible for:
- Develop statistical credit loss models using a large relational database of residential mortgages.
- Apply statistical and programming knowledge, using R and SQL, for the purpose of credit loss forecasting: including writing code, estimating model parameters, and working with the model validation team.
- Summarize insights and present key findings to business stakeholders and senior management
- Respond to model scrutiny and inquiries from both internal and external validators as well as federal regulators to ensure conceptual soundness, prediction accuracy, and robustness
- Perform regression diagnostics such as stationarity, residual correlation, heteroscedasticity, normality of residuals, multi-collinearity, highly influential observations, and overfitting
The Successful Applicant
The successful candidate will have:
- masters degree in analytics, mathematics, econometrics or financial engineering
- team oriented and willing to juggle multiple projects and deadlines simultaneously
- strong skill set in credit risk modeling using large data bases of loan
- Strong modeling skills in R, SQL, SAS, or Python
What's on Offer
Competitive pay with bonus potential and competitive benefits.