Firma
Our client is a global professional services provider offering research, analytics, and data management services. They’re powered by mind+machine – a unique combination of human expertise and best-in-class technologies that use smart algorithms to simplify key tasks.
You will be working with the Model Risk Management group of a global investment bank with which we have an existing relationship. As a first assignment, You will be managing engagement with the model validation team of the bank and work on validating the Murex model. The role requires a good understanding of SIMM, VaR, FRTB, market risk models, pricing, and derivative model structures. Prior experience working on Murex is a must for this role.
Zakres obowiązków
- Work specifically on validating market risk models.
- Interact with Model Developers, Model owners, and other stakeholders to efficiently maintain the Model risk management process
- Responsible for review, critical assessment, and challenge of models on conceptual soundness, assumptions, and limitations of the model along with documentation of the validation process
- Responsible for review and critical assessment of ongoing model monitoring reviews
- Responsible for performing validation of Murex pricing and risk models
Wymagania
- 2 - 4 years of experience in Global Banks / Risk Consultancies
- Experience with the Murex system is a must for this role
- Validation/Development of Market Risk Models such as VaR Models, SVaR, Taylor VaR, RNIV, SIMM, SIMM breaches, backtesting, Capital Impact Assessment, Quantitative risk Analysis
- Experience in the development and implementation of effective testing plans to critically challenge models through empirical analyses and to verify model implementations
- Experience with programming languages such as Python, C++, C#, and Java to repurpose Python code for VaR calculation engine or building VaR calculation engine from scratch
- Validation / Development of SIMM model while monitoring SIMM Initial margin, SIMM 10D VaR, Risk Not in SIMM
- Experience in monitoring VaR model – back-testing, statistical analysis, Risk not in VaR, Taylor VaR implementation and benchmarking, preparing VaR dashboards
- Strong oral and written communication skills, including the ability to document analytical results suitable for audiences of all technical levels
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