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Quantitative Risk Specialist, Matlab, R, SAS, Stata, Stress Testing
Eingestellt von Manpower Switzerland
Gesuchte Skills: Matlab, Engineering, Vba, Client
Projektbeschreibung
We are looking for an Quantitative Risk Specialist in Zurich. (5 month project)
Our client develop and maintain a suite of scenario-aligned risk category stress models and support diverse other stress-related activities.
KEY RESPONSIBILITIES
- a Master's or PhD degree in applied quantitative discipline (eg Econometrics, Statistics, Financial Engineering, Economics, Finance)
- some experience in Stress Testing/Economic Capital or other areas of risk methodology
- experience in Credit Risk (essential)
- sound knowledge of statistical and econometric methods and their application
- some experience in end.to-end model testing
- IT flair and programming knowledge (experience in writing code is essential)
- strong analytical, conceptual and organizational skills with the ability to work to tight deadlines
- good general understanding and interest in (macro-) economic mechanisms and their influence on financial markets
- experience with handling large datasets is a plus
REQUIREMENTS
- a Master's or PhD degree in applied quantitative discipline (eg Econometrics, Statistics, Financial Engineering, Economics, Finance)
- experience in Stress Testing/Economic Capital or other areas of risk methodology preferred
- sound knowledge of statistical and econometric methods and their application
- IT flair and programming knowledge. Experience in writing code is essential
- strong analytical, conceptual and organizational skills with the ability to work to tight deadlines
- good general understanding and interest in (macro-) economic mechanisms and their influence on financial markets
- experience with handling large datasets is a plus
- proficient user of statistical software and programming (eg. Matlab, VBA, SAS, R, C++)
- Understanding of Pillar I and II methodologies for Credit Risk
- a great communicator (and you know how to handle challenging situations)
- team-orientated, while able to complete tasks independently
- fluent in English, additional languages are welcome
Our client develop and maintain a suite of scenario-aligned risk category stress models and support diverse other stress-related activities.
KEY RESPONSIBILITIES
- a Master's or PhD degree in applied quantitative discipline (eg Econometrics, Statistics, Financial Engineering, Economics, Finance)
- some experience in Stress Testing/Economic Capital or other areas of risk methodology
- experience in Credit Risk (essential)
- sound knowledge of statistical and econometric methods and their application
- some experience in end.to-end model testing
- IT flair and programming knowledge (experience in writing code is essential)
- strong analytical, conceptual and organizational skills with the ability to work to tight deadlines
- good general understanding and interest in (macro-) economic mechanisms and their influence on financial markets
- experience with handling large datasets is a plus
REQUIREMENTS
- a Master's or PhD degree in applied quantitative discipline (eg Econometrics, Statistics, Financial Engineering, Economics, Finance)
- experience in Stress Testing/Economic Capital or other areas of risk methodology preferred
- sound knowledge of statistical and econometric methods and their application
- IT flair and programming knowledge. Experience in writing code is essential
- strong analytical, conceptual and organizational skills with the ability to work to tight deadlines
- good general understanding and interest in (macro-) economic mechanisms and their influence on financial markets
- experience with handling large datasets is a plus
- proficient user of statistical software and programming (eg. Matlab, VBA, SAS, R, C++)
- Understanding of Pillar I and II methodologies for Credit Risk
- a great communicator (and you know how to handle challenging situations)
- team-orientated, while able to complete tasks independently
- fluent in English, additional languages are welcome
Projektdetails
Geforderte Qualifikationen
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Kategorie:
IT Entwicklung, Ingenieurwesen/Technik