Risk Analytics - Model Building, Model Development -M/SM/AVP/VP

Job Description

Job description Role & responsibilities Develop predictive models using latest machine learning / statistical methods across the domains of Risk, customer & sales Define and establish robust model evaluation & governance framework Engage with the Risk & Model Committees Responsible for the end-to-end development and implementation of all scorecards/risk monitoring framework across businesses Stakeholder relationship management & control aspects of analytical project delivery Key Competencies / skill set : Should be a subject matter expert in the domain of credit risk Strong statistical knowledge and demonstrated hands-on experience in model development & management Working knowledge of R, Python or SAS is a must. Should be able to anchor stakeholder engagements Very strong presentation & communication skills Desired Candidate Profile Similar Profiles from Banks Resilience & ability to work in a dynamic environment Technical competence will be an important selection criterion Demonstrated hands-on experience in loss forecasting, scorecards & advanced analytics use cases Qualifications Post-graduation in Statistics or Economics or Quantitative Economics or Computer Science OR MBA (Finance / Quantitative Methods) Predictive model development Logistic/Linear Regression, Clustering, D-tree, Feature Selection, PCA SVM, Random Forest, Gradient Boost Experience : Candidate is required to have minimum 2-15 years of relevant work experience in statistical modeling in a Bank