ALM & Capital Model Validator
Your working environment
The ALM & Capital Model team validates the models employed for managing the market (e.g. interest rate) and liquidity risks associated with the products in the banking book of the Bank. The scope of this validation team includes a variety of models ranging from the behavioural Interest Rate Mortgage Model to Market Risk in the Banking Book Economic Capital model.
The validator in this team has a key role of:
- Assessing the quality of the data used for the development of the prototype model;
- Examining the correctness of the methodology and assumptions;
- Forming an independent opinion on the model's performance;
- Assessing the compliance of the model with respect to internal and external regulations;
- Checking the final implementation of the model in the production environment.
Your profile
General:
- University degree in a quantitative discipline, e.g. (financial) mathematics, (theoretical) physics, econometrics or similar, at least at Masters level. A PhD and/or additional. Qualification (e.g. FRM, CFA, CQF certificates, or second Master degree in economics, finance or similar) is desirable.
- At least 4 years of relevant work experience in a quantitative role in the financial industry (e.g. modeller, model validator, quantitative risk manager, quant developer, quantitative consultant) and/or in related research.
- Full professional proficiency of English, capable to influence internal stakeholders.
Specific knowledge:
- Knowledge, understanding of and experience with
- Time-series analyses and forecasting;
- Monte-Carlo simulation;
- Behavioural models;
- Econometrics and/or fundaments of Mathematical Finance, Statistical and Numerical Methods used in Quantitative Finance.
- Experience with and understanding of Interest Rate Risk, Liquidity Risk, Funds Transfer Price and/or Economic Capital models.
- Experience in handling, pre-processing and assessing the quality of (large) data sets.
- Experience with modern programming languages, e.g. Python, MATLAB, C++ and/or database tooling, e.g., SQL, SAS and their application in statistical analysis.
- Working knowledge of MS Office programmes, in particular Word and Excel.
