Assistant Manager - Credit Risk

Description

• Should have prior experience in Model Risk Management (Model development/model validation) with GSIBs or Indian Banks 
• Good understanding of ESG and Climate Risk models such as Climate Change simulation models, counterparty-level transition & financial models, nature hazard models, physical risk models, climate scenario models, emission pathway models
• Should have prior experience in climate related datasets such as Exiobase, S&P Trucost and climate scenarios such as NGFS, IEA, etc.
• Should have supported central data and modelling teams to source required data, develop climate scenario models, and determine how to best integrate climate risk data into BAU credit risk models.
• Candidate should have worked on Credit (retail or wholesale) model development/validation. Candidate should understand different banking portfolios such as Credit Cards, Mortgage, PIL, Corporate, NBFI etc. He/she should be able to develop/validate models used for different regulatory perspective such as FED, EBA, PRA, IFRS-9 regulations.
• Proven expertise in using statistical algorithms for solving diverse business challenges and creating significant business value.

Responsibilities

• Should have prior experience in Model Risk Management (Model development/model validation) with GSIBs or Indian Banks 
• Good understanding of ESG and Climate Risk models such as Climate Change simulation models, counterparty-level transition & financial models, nature hazard models, physical risk models, climate scenario models, emission pathway models
• Should have prior experience in climate related datasets such as Exiobase, S&P Trucost and climate scenarios such as NGFS, IEA, etc.
• Should have supported central data and modelling teams to source required data, develop climate scenario models, and determine how to best integrate climate risk data into BAU credit risk models.
• Candidate should have worked on Credit (retail or wholesale) model development/validation. Candidate should understand different banking portfolios such as Credit Cards, Mortgage, PIL, Corporate, NBFI etc. He/she should be able to develop/validate models used for different regulatory perspective such as FED, EBA, PRA, IFRS-9 regulations.
• Proven expertise in using statistical algorithms for solving diverse business challenges and creating significant business value.

Qualifications

• Master's / Bachelor’s degree in mathematics/Statistics/Economic/Engineering/Computer Science/Management or any other quantitative fields of study
• Strong quantitative and analytical skills with attention to detail and accuracy
• SAS, Python, R 
• Candidates with SCR certification or any other certification on climate risk will be preferred.