Credit Risk Lead/Manager

Job Description

Evalueserve is a global leader in delivering innovative and sustainable solutions to a diverse range of clients, including over 30% of Fortune 500 companies. With presence in more than 45 countries across five continents, we excel in leveraging state-of-the-art technology, artificial intelligence, and unparalleled subject matter expertise to elevate our clients business impact and strategic decision-making. We have 4,500 talented professionals operating across 45 countries, including India, China, Chile, Romania, the US, and Canada. Our global network also extends to emerging markets such as Colombia, the Middle East, and the rest of Asia-Pacific. Recognized by Great Place to Work in India, Chile, Romania, the US, and the UK in 2022, we offer a dynamic, growth-oriented, and open culture that prioritizes flexible work-life balance, diverse and inclusive teams, and equal opportunities for all.As a Sr. Analyst/Lead/Manager at Evalueserve in Gurugram, you will be a part of the Risk and Quant Solutions (RQS) department, which is one of the fastest growing practices at Evalueserve. You will address some of the worlds largest financial needs with technology-proven solutions, solving banking challenges and improving decision-making with award-winning solutions.### Role Overview:- Model development for Retail and wholesale model development- Scorecard model development- IFRS 9/ CECL model development### Key Responsibilities:- Excellent knowledge of credit risk models for the wholesale portfolio, model structure, variable treatments, variable data framework, and model development process.- Extensive knowledge of statistical methods and tools such as logistic regression, Bayesian statistics, the Markov chain process, and time series analysis.- Knowledge of credit risk models PD, EAD, and LGD, scorecards, IFRS 9, Basel II IRB approach for credit risk, logistic and linear regression models.- Extensive knowledge of SAS, Python (including OOP), statistical procedures, and automation capabilities in SAS and Python.- Understanding of various credit risk model constructs and credit risk modeling frameworks.- Understanding of the consumption layer of the curated data, i.e., model development for credit risk models, especially IFRS9, stress testing, and AIRB (PD, LGD, and EAD models).If you are interested in this role, you can also share your resume directly to [HIDDEN TEXT]. Evalueserve is a global leader in delivering innovative and sustainable solutions to a diverse range of clients, including over 30% of Fortune 500 companies. With presence in more than 45 countries across five continents, we excel in leveraging state-of-the-art technology, artificial intelligence, and unparalleled subject matter expertise to elevate our clients business impact and strategic decision-making. We have 4,500 talented professionals operating across 45 countries, including India, China, Chile, Romania, the US, and Canada. Our global network also extends to emerging markets such as Colombia, the Middle East, and the rest of Asia-Pacific. Recognized by Great Place to Work in India, Chile, Romania, the US, and the UK in 2022, we offer a dynamic, growth-oriented, and open culture that prioritizes flexible work-life balance, diverse and inclusive teams, and equal opportunities for all.As a Sr. Analyst/Lead/Manager at Evalueserve in Gurugram, you will be a part of the Risk and Quant Solutions (RQS) department, which is one of the fastest growing practices at Evalueserve. You will address some of the worlds largest financial needs with technology-proven solutions, solving banking challenges and improving decision-making with award-winning solutions.### Role Overview:- Model development for Retail and wholesale model development- Scorecard model development- IFRS 9/ CECL model development### Key Responsibilities:- Excellent knowledge of credit risk models for the wholesale portfolio, model structure, variable treatments, variable data framework, and model development process.- Extensive knowledge of statistical methods and tools such as logistic regression, Bayesian statistics, the Markov chain process, and time series analysis.- Knowledge of credit risk models PD, EAD, and LGD, scorecards, IFRS 9, Basel II IRB approach for credit risk, logistic and linear regression models.- Extensive knowledge of SAS, Python (including OOP), statistical procedures, and automation capabilities in SAS and Python.- Understanding of various credit risk model constructs and credit risk modeling frameworks.- Understanding of the consumption layer of the curated data, i.e., model development for credit risk models, especially IFRS9, stress testing, and AIRB (PD, LGD, and EAD models).If you are interested in this role, you can also share your resume directly to [HIDDEN TEXT].

Keyskills :
Credit Risk ModelsLogistic RegressionBayesian StatisticsTime Series AnalysisSASPythonStress TestingStatistical MethodsMarkov Chain ProcessIFRS 9Basel II IRB