Development and maintenance of AIRB/IFRS9 credit risk models (PD, LGD, CCF) for multiple portfolios and IFRS9 Stage Transfer logic
Group-wide methodological responsibility for quantitative credit risk
Forward-looking construction of a cross-functional methodology architecture
Ensuring compliance with regulatory/accounting standard requirements (Basel / IFRS9 etc.) and EBA GL
Programming of prototypes for impact and scenario analysis in different programming languages ( R/Python, SAS/SQL )
Data preparation, statistical and empirical investigations, handling of very large amounts of data, their aggregation and evaluation
Preparation of technical specifications, presentations and documentation of quantitative credit risk forecasting models
Internal and external communication, including auditors, regulators, external partners and rating agencies
Requirements
Master degree with very good grades in mathematics, physics, econometrics or related fields
Very good mathematical-statistical skills as well as knowledge of the mathematical-statistical basis of model development (multivariate statistical methods, stochastic processes, etc.)
Sound knowledge of data modelling software and coding ( R/Python, SAS/SQL ), experience in analysis of huge data sets
Strong analytical skills and attention to details
English C1 level
Knowledge of regulations from credit risk models area (CRR, EBA GL, IFRS9) will be an asset