We are looking for you, if you have:

• an academic degree (BSc or MSc) in econometrics, quantitative methods, statistics, IT, mathematics, physics or a similar quantitative field,
• sound knowledge of interest rate risk measures (BPV, VaR, NII, EVE) and sources,
• experience in modelling of interest rate risk in the banking book (e.g. NMDs, interest rate dynamics, interest rate curves, stochastic interest rate models),
• understanding banking and financial market products e.g. options, interest rate swaps,
• sound knowledge of statistical modelling and econometric methods,
• experience with statistical programming (e.g. Python, R).

Youll get extra points for:

• experience in the development, implementation and/or validation of behavioural models such as prepayment models,
• replication (hedging) models,
• understanding banking and financial market products e.g. options, interest rate swaps,
• knowledge of and experience with advanced statistical techniques such as, Monte Carlo, numerical methods, stochastic interest rates, etc.,
• experience with databases, data modelling, data preparation and data quality control is considered a plus,
• experience with Git, Azure DevOps,
• understanding Scrum and Agile Way of Work.

Your responsibilities:

• performing quantitative analysis,
• improving model methodology,
• model implementation and development of tools (Python),
• assessing model performance - backtesting, monitoring, benchmarking,
• technical reporting - model documentation.

Information about the Team:

The Financial Risk Model Development department is an international team of highly qualified professionals. Our expertise lies in the development and management of credit, market and operational risk models. The Risk Hub Warsaw model development team will be performing model development activities for models throughout ING, working closely together on international projects with the teams in Amsterdam.

The developed ALM models are core to the success of ING and include behavioural (e.g. prepayment), replication (hedging) and stress testing models. The models are used by all local Risk Management units within ING.

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

The role naming convention in the global ING job architecture will be “Model Developer III”.