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Job Location | Mumbai City |
Education | Not Mentioned |
Salary | Not Disclosed |
Industry | Banking / Financial Services |
Functional Area | Sales / BD |
EmploymentType | Full-time |
Does risk modelling excite you Are you an innovative thinker and interested in risk topics Do you know how to work well within a team to develop and deliver high quality solutions The role as Risk Modeler in the Risk Analytics team primarily involves: contribute to the constant refinement and improvement of the credit risk methods, in particular our tools and models develop risk-based monitoring tools both on a portfolio as well as on a single client level (e.g., concentration and/or liquidity) from which steering actions for our portfolios will be derived collaborate with risk officers, business managers, Risk IT, Change Operations and other stakeholders supporting the proper implementation and execution of risk models and support regulatory exercises support senior management with portfolio as well as single client analysis based on specific risk scenarios bring innovation and of automation by actively elaborating and proposing improvements to our model maintenance and development process implement prototype models in R or SAS, before being embedded into the productive risk infrastructureYour teamYou ll be working in the Non-Lombard Credit Methodology P&C Confirmations team in Mumbai, India. Your main responsibilities will be to maintain and regularly update our methodologies for lending value determination as well as in the future for PD/LGD modelling. Our modelling framework captures all businesses world-wide ranging from retail clients to complex structured lending solutions for UHNW clients. You will be working with key stakeholders within our Global Wealth Management business and Personal & Corporate Banking on both the risk and the business side to deliver state of the art methodologies and support new business initiatives., master s or PhD degree in a quantitative field like Financial Mathematics, Statistics or Econometrics sound practical understanding of financial markets and products prior working experience in a credit risk environment would be beneficial together with knowledge of regulatory practice ability to apply techniques from numerical analysis, statistics and financial mathematics to solve practical problems experience with large data sets / Big Data cooperativeness and team-orientation, while able to complete tasks independently with a high quality standard pro-activeness in taking new initiatives and carrying them through completions experience with high-level programming language, and knowledge of statistical modelling software (e.g., SAS, R, MatLab) excellent communication skills with colleagues at all levels in the organization ability to explain technical topics clearly and intuitively, both written and orally fluency in English, both in oral and written form*#LI-SS1
Keyskills :
acquisitionbusiness strategyclusteringdirect maildirectioncredit riskrisk modelsnew businessrisk analyticsmonitoring toolscorporate bankingsenior management