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
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