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At ING Tech Poland and ING group we follow the Agile approach and mindset. We use flexible frameworks like Scrum and Kanban at our everyday work. We are innovative and we trust people we work with. The broad autonomy our employees have, stimulates motivation and creativity what allows us to adapt to the changing requirements of business partners. Small units called squads are the core of our organization. They have clear vision of products, overcome challenges autonomously and based on team cooperation, work out the most flexible and effective way of working.

The Financial Risk Model Development department is an international team of 200 highly qualified professionals. Our expertise lies in the development and management of credit risk, ALM and operational risk models. To further strengthen and develop the modelling capabilities, ING decided to setup Risk Hub Warsaw. The Risk Hub Warsaw model development team performs model development activities for models throughout ING, working closely together on international projects with the teams in Amsterdam.

The developed credit risk models are core to the success of ING and include IRB and IFRS9 models (PD, LGD, EAD) for retail and wholesale portfolios, as well as non-regulatory models. The models are used by all local Risk Management units within ING.

As a specialist in credit risk modelling, you will be given the opportunity to gain further experience in credit risk modelling topics, using state-of-the-art modelling methods, tooling and data processing technologies.

• An academic degree (BSc or MSc) in econometrics, quantitative methods, statistics, mathematics, physics or a similar quantitative field
• Sound knowledge of statistical modelling and econometric methods
• Experience with statistical programming (e.g. Python, SAS)
• Knowledge and experience with credit risk model development or validation, regulatory (Basel/IRB, IFRS9) or non-regulatory (e.g. credit approval models) or modelling of recovery processes

• Knowledge of financial regulation (Basel, EBA, IFRS9)
• Knowledge of and experience with advanced statistical techniques such as Bayesian modelling, Monte Carlo, neural networks, etc.
• Experience with databases, data modelling, data preparation and data quality control is considered a plus
• Professional certification FRM/PRM/CFA or CQF

• Strong analytical and problem-solving capabilities
• Communication and presentation skills, advanced level of English (C1 or above)
• Independent, creative and pro-active mind-set
• Keen on innovation
• Analytical and critical attitude