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| Job Location | London |
| Education | Not Mentioned |
| Salary | Competitive salary |
| Industry | Not Mentioned |
| Functional Area | Not Mentioned |
| Job Type | Permanent , full-time |
Our client, a highly ranked provider of high end research & analytics services to large Investment Banks is looking to hire two individuals for this exciting opportunity. They are also open to both contractors and individuals looking for permanent roles.The role can be based in Dublin or London and the must haves for this role are strong SAS skills, experience of regulatory testing and scenario expansion models. Job Duties Develop and execute macroeconomic scenario expansion models for the EBA stress test,covering the latest climate risk scenarios. Model development and execution in SAS/Excel covering a range of modelling techniques. Delivery of model documentation to articulate the scenario expansion and forecasting methodology. The candidates are requiredto have sound knowledge in the following models: Macroeconomic scenario expansion Climate risk modelling (physical and transition risk) Credit risk PD and LGD models (RWA and IFRS9) Skills Required: A minimum of 5-6 years experience within a financial servicesinstitution or consultancy in a model development or validation function. A Masters or PhD degree in a quantitative discipline such as Financial Engineering, Econometrics, Mathematics, Data Science, Mathematics, Engineering or Physics; Preferably a professionalqualification such as CQF, PRM, FRM or CFA. Hands on experience working on SAS and Excel is essential. Hands on experience with Python is desirable. A strong understanding of the ECB and EBA regulatory stress testing exercises, including the latest changespertaining to climate risk scenarios. A strong understanding of forecasting techniques for scenario expansion such as proxy mapping, linear/cubic spline interpolation and multivariate regression for macroeconomic variables, interest rates, equity prices, FX,commodity prices and credit spreads. Strong understanding of climate risk modelling pertaining to physical and transition risks. Strong understanding of PD and LGD models for RWA and IFRS9 provisions computation (linked to underlying macroeconomic variables).Strong understanding of the key stages of the model lifecycle. Ability to interrogate and manipulate large volumes of data. Ability to liaise with technical teams to ensure that deliverables are met in accordance with project timescales. Strong communicationskills and ability to describe model outputs to a technical and non-technical senior management audience. Excellent analytical and creative problem solving skills. Ability to write coherent model development and procedures documentation and provide trainingto support adoption of changes and embedding within the business. Qualifications: Masters or Bachelors degree in Finance, Economics, Econometrics, Engineering, Science, Financial Engineering, Statistics, Mathematics or Data Science. CQF, FRM, PRM or CFApreferred.