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Quantitative Credit Risk Modeller

Posted on Sep 23, 2020 by Experis AG

Zürich, Switzerland
IT
Immediate Start
Annual Salary
Contract/Project


Quantitative Credit Risk Modeller


Experis is the global leader in professional resourcing and project-based workforce solutions. Our suite of services range from interim and permanent recruitment to managed services and consulting, enabling businesses to achieve their goals. We accelerate organisational growth by attracting, assessing and placing specialised professional talent.


On behalf of our client, a leading financial institution in Zürich, we are looking for an Investment Banking Risk Modeller.


Responsibilities:



  • Development, prototyping, and implementation of methodologies for back testing of Monte Carlo counterparty credit risk models

  • Counterparty credit exposure calculations according to Basel 3/CRD4

  • Development of capital relevant risk methodologies in the derivatives area for FINMA, PRA, and SEC

  • Possibility to support IT in the strategic implementation of complex risk and simulation systems

  • Close collaboration with several internal stakeholders around the globe (Front Office quants, financial accounting, CVA desk and other risk departments)


Skills:



  • At least 3 years of relevant experience in a quantitative discipline

  • Master's or PhD degree in a related quantitative discipline (eg physics, mathematics, engineering, or computer science)

  • Sound knowledge in at least one of the following topics: Statistical analysis, Monte Carlo simulations, derivative pricing/modelling, risk modelling, machine learning

  • Working knowledge of at least one programming language of C/C#/C++/Python/R/Java is a must, VBA, SQL, and Office package is highly recommended

  • Excellent communication and presentation skills as well as strong team-player skills

  • Fluency in English is mandatory


Interested in this opportunity? Kindly send us your CV today through the link in the advert. However should you have any questions please contact Jane Leese.






Reference: 954984675

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