Risk Modelling Consultant Risk Modelling Consultant …

Greifenberg
in Singapore, Singapore, Singapore
Permanent, Full time
Last application, 13 Aug 20
Competitive
Greifenberg
in Singapore, Singapore, Singapore
Permanent, Full time
Last application, 13 Aug 20
Competitive
Greifenberg
A leading global consulting firm, is looking for a Risk Modelling Consultant to strengthen their GRC team in Singapore. It is with a Consultancy (not a Big Four) that distinguishes itself by: 1. Real and substantive knowledge 2. Listening to the customer and looking for the solution together instead of slightly adjusting its 'own' model and pushing it into the organization (which sometimes seems to be the case with other Consultancies) 3. Jointly (with the customer) put together a solution, so that the solution is a more permanent one 4. Soft skills - involved, authentic and professional

The group has grown rapidly in terms of their activities, track record and presence and has succeeded in breaking new ground with their innovative business model within the following consulting solutions; technology, business process, analytics, risk, compliance, transactions and internal audit.

Profile needed:

  • Ph.D. (optional) or MSc in a quantitative subject (Mathematics, Statistics, Applied Mathematics, Mathematical Finance, Physics, etc)
  • Understanding of Monte-Carlo Methodologies
  • Experience in risk-modelling (model development or validation)
  • Experience in market risk or/and counterparty risk modelling
  • Experience with other risk models (Economic Capital, Stress Testing, etc.)
  • Strong background in Math and Probability theory - applied to finance.
  • Good understanding of financial products.
  • Good programming level in Python or R or equivalent.
  • Awareness of the latest technical developments in financial mathematics, pricing, and risk modelling
  • Up-to-date knowledge of regulatory capital requirements for market and credit risk

Responsibilities

  • Quantitative analysis and review of model frameworks, assumptions, data, and results
  • Designing, modelling and prototyping challenger models when required
  • Continuous interaction and collaboration with stakeholders from a wide range of internal business areas, internal and external audit as well as supervisory authorities
  • Testing models numerical implementations and reviewing documentations
  • Checking the adherence to governance requirements
  • Documentation of findings invalidation reports, including raising recommendations for model improvements
  • Ensuring models are validated in line with regulatory requirements and industry best practice
  • Tracking remediation of validation recommendations
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