6 - 10 years of experience in ML models in Credit Risk (Banking domain only) - C2 ( C1 can be considered only if very good profile)
Tool - Well-versed in Python, SQL , excel, PPT ( Good to have knowledge of cloud platform , SAS, PySPark)
Skillset:
Hands-on in development of ML models in Credit Risk area - Application scorecard, Behaviour scorecard , Fraud Scorecard, Collection scorecard, Income estimation, Credit Line optimization ( have worked on any or few of them) -(Good to have experience in building marketing ML models)
Strong foundation in predictive modeling and machine learning along with deep understanding of credit risk management. Design ML solutions to address business needs on Credit risk side. Experience with supervised and unsupervised ML algorithms such as Random Forest, GBM, XGBoost, CNN, RNN, SVM, Markov process etc. Should be able to synthesize the findings at various points through model development process to share actionable insights with senior leadership and other stakeholders.
Good communication skillset along with structured thought process with experience in handling senior stakeholder.
