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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