Perform analysis and conduct empirical research on large-scale data and analyze risk indicators of the bank through relevant mathematical-statistical models
Build, validate, document, implement and rebuild: Credit risk models (retail loan origination models, business customer scoring/rating models and loan behavior scorecards), collective Provision and Expected Loss methodologies (PD, LGD, forward-looking model estimations)
Develop risk models and tooling to accommodate new products or strategies and enhance existing models where necessary
Investigating and applying different methods to market and operational risk measurement (VAR and etc.)
Identify stress scenarios on portfolios and make suggestions for applying stress testing results to the allocation of capital reserves
Perform ad-hoc analysis on large sets of market data and position information
Ensure risk models are properly documented and periodically back-tested
High education degree in mathematics, econometrics, quantitative methods or related fields
Ability to apply different regression models (e.g., linear, non-linear, log and etc.)
Up to 1 year of experience modelling, model validation or quantitative risk function
Analytical skills and competence to interpret database to get logical results
Ability to prepare and present analysis for different purposes
Good programming skills, preferably in Python, R
Knowledge of Azerbaijani, English and/or Russian languages
Have a professional and transparent business ethics