Risk Model Development Specialist

Purpose

As Risk Model Development Specialist, you will be part of the Credit Risk and Enterprise Risk Modeling team which has the responsibility to develop and apply the methods used in measuring and assessing credit risk at the Group level as well as to submit updates to the competent Committees of the Bank and Group Companies. Additionally, the Credit Risk and Enterprise Risk Modeling Business Area also develops credit risk models used in impairment testing at the Group level, in accordance with International Accounting Standards.

Ideally, you should possess advanced problem-solving and analytical skills along with sound judgment and critical thinking and should have the ability to communicate advanced concepts in a concise and logical way. This role will suit you if you thrive on delivering results in a fast-paced environment where your work has a high impact.

What you will be doing

• Development of statistical models and AI algorithms focused on classification tasks, machine translation and language generation for credit risk assessment in all aspects of the Group products and activities.
• Estimation of all the credit risk parameters (PD, LGD, EAD) in compliance with the regulatory frameworks and in line with industry best practices.
• Participation in the design and implementation of appropriate methodologies through effective programming to manipulate, analyse and model large volumes of data as well as manage credit risk.
• Implementation of regular reviews and updates of model documentation (methodology guide, user guide, policy documents, etc.).
• Research of best practices in applying statistical and econometric methods in credit risk modelling.
• Monitoring of the deployment of credit risk models in the IT Systems of the Bank.

What you need to have

• A Bachelor’s degree in a quantitative discipline e.g. Engineering, Statistics, Mathematics, Quantitative Finance, Computer Science, or in any other related field.
• A Master’s or PhD degree in any of the abovementioned fields.
• Two (2) to six (6) years of professional experience in building and implementing credit risk models in an IRB or IFRS9 context.
• Expertise in the use of analytics tools such as SAS, SPSS Modeler/ Statistics.
• Previous experience with processing massive datasets (structured vs unstructured data) and drawing insightful conclusions.
• The following will be considered as additional assets: (1) Experience in procedural and imperative programming languages (e.g., SQL, PL/SQL, T-SQL etc.) and use of databases. (ii) Strong coding skills in the following programming scripting languages: R, Python, C++. (iii) A good understanding of Machine Learning, deep learning and NLP algorithms and methodologies.
• Agile project/product development employing DevOps practices (e.g., automated testing).
• Project Management skills coupled with strong business acumen in terms of comprehending the business and operational impact of risk management decisions.
• Excellent command of the English language (both written and spoken).

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