Quantitative Risk Specialist

  • UBS Business Solutions AG
  • Zürich, Switzerland
  • 09/09/2019
Full time Data Science Data Engineering Data Management Statistics

Job Description

Your role:

Does quantitative 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?

Then we are looking for you to:

– Develop methodologies for quantitative modelling of the probability of default (PD) and loss-given-default (LGD) for our Lombard portfolio for UBS Group
– Use techniques from quantitative risk management, financial mathematics and econometrics to develop and change existing risk models.
– Bring innovation to the Risk Methodology Group in the development, refinement and implementation of risk models
– Implement prototype models in R, MatLab or SAS, before being embedded into the productive risk infrastructure
– 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

Your team :

You’ll be working within the PD & LGD Lombard Credit Methodology team in Zürich, Switzerland.
Your main responsibilities will be to develop and maintain UBS’s Advanced Internal Rating Based models covering our Lombard business. The framework captures all Lombard businesses world-wide ranging from retail clients to complex structured lending solutions for large UHNW clients. You will be working with key stakeholders within our Global Wealth Management business on both the risk and the business side to deliver state of the art methodologies and support new business initiatives.

Your expertise :

– A Master's degree in an applied quantitative discipline (e.g. Econometrics, Statistics, Financial Engineering, Economics, Finance)
– Ideally 1-3 years' of experience in credit risk modelling or other areas of risk methodology and/or model development
– Sound knowledge of statistical and econometric methods and their application
– Strong IT / programming skills. Previous experience and ability to implement models in a programming language (e.g., R, MatLab) is essential and experience with handling large datasets is a plus
– Strong analytical, conceptual and organizational skills with the ability to work under tight deadlines
– Interest in placing model development activities within the bigger picture of the organisation
– Ability to influence and convince key stakeholders within the model development process