Key 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 riskStrong statistical knowledge and demonstrated hands-on experience in model development & managementWorking knowledge of R, Python or SAS is a must.Should be able to anchor stakeholder engagementsVery strong presentation & communication skillsDesired Candidate Profile
Similar Profiles from BanksResilience & ability to work in a dynamic environmentTechnical competence will be an important selection criterionDemonstrated hands-on experience in loss forecasting, scorecards & advanced analytics use casesQualifications
Post-graduation in Statistics or Economics or Quantitative Economics or Computer Science OR MBA (Finance / Quantitative Methods)Predictive model developmentLogistic / Linear Regression, Clustering, D-tree, Feature Selection, PCASVM, Random Forest, Gradient BoostExperience :
Candidate is required to have minimum 2-10 years of relevant work experience in statistical modeling in a Bank
Industry Preferable :
Banking