Requires a Bachelors degree, or foreign equivalent, in Statistics, Economics, or related field and 5 years of progressive, postbaccalaureate experience as Credit Portfolio Analyst or related position involving development of credit risk and statistical models using Logistic and Linear Regression, Time Series Models and machine learning methodologies. 5 years of experience must include Developing credit risk and statistical models using Logistic Regression, Linear Regression, Time Series Models and machine learning methodologies Gradient Boosting, Artificial Neural Networks; Performing quantitative credit risk analysis for consumer banking to identify key risks from business strategy and activities; SAS, SAS Macros, R, Python, SQL, Excel, VBAMacros, PowerPoint; Segmentation techniques using Decision Trees and data mining using SAS EMiner, Classification Regression Trees CART and CHAID methodology; Model validation, performance tracking and model reviews to assess sensitivity, back test performance, calibration requirement, outoftime testing for credit risk models; Big Data environments and platforms handling large data sets to organize, interpret, analyze and summarize huge volumes of credit card data; Data mining and analysis, data integrity QAQCreconcilements; Creating and presenting technical model documentation reports for validation; Implementing statistical and segmentation models for consumer banking credit cards. Proof of full vaccination against COVID19 required prior to commencing employment.
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