Model Developer Interest Rate & Inflation

As a Model Developer specializing in Interest Rate & Inflation at ING, your responsibilities will include developing calculation methodologies for valuation adjustment models, creating Trading Risk methodologies such as Incremental Risk Charge and VaR scenario specifications, and designing model monitoring processes. You'll also be tasked with implementing production checks and providing quantitative support to risk managers and traders, making your role pivotal in the risk management framework.

Candidates interested in the Model Developer role at ING should have either a PhD or MSc in a quantitative field such as mathematics, physics, or statistics. You should also possess between 7 to 10 years of experience in quantitative roles, specifically in Market Risk models and Counterparty Credit Risk models. Experience with Python or C++ is essential, particularly for derivatives pricing models in Interest Rate & Inflation or similar asset classes.

ING is dedicated to supporting the personal and professional growth of its employees, including Model Developers. You will receive access to challenging work, a robust career development framework, and opportunities for continuous learning. The hybrid working environment also allows for flexibility in balancing your professional responsibilities with your personal commitments.

At ING, a Model Developer can expect an informal yet dynamic working environment. You’ll be surrounded by innovative colleagues who value teamwork and collaboration. The culture encourages asking questions and brainstorming, making it a great place for professionals eager to make an impact while enjoying their work.

As a Model Developer at ING, you will leverage state-of-the-art modelling methods, tooling, and data-processing technologies. Familiarity with programming in Python or C++ is crucial, as you will build and implement various risk models related to Trading and Counterparty Credit Risk. Additionally, you will engage with various analytical tools to analyze methodologies used for risk assessment and market data proxies.

When answering this question, highlight your specific experience with Market Risk models, detailing the types of models you've developed and implemented. Speak about your understanding of the methodologies involved and how you've contributed to managing market risk in previous roles.

Discuss the specific methodologies you have employed in your valuation of trading risks, such as Incremental Risk Charge or VaR scenarios. Make sure to elaborate on how you implemented these methodologies and the outcomes derived from them to reflect your practical experience.

Explain the importance of model monitoring in risk management. Highlight how continuous monitoring helps in validating the performance of models and ensures compliance with regulatory requirements, which can minimize potential risks for the organization.

Be prepared to give concrete examples of how you've used Python or C++ for developing risk models. Describe specific projects, any libraries you used, and how your coding capabilities directly contributed to the development of robust models.

Demonstrating your knowledge about the Fundamental Review of the Trading Book (FRTB) is crucial. Discuss its significance in financial regulation, focusing on how it affects Market Risk models and your understanding of its key components.

Outline a structured approach for developing a new pricing model. Mention steps such as understanding market needs, designing the model based on market data, performing backtesting, and collaborating with stakeholders during the development process.

Share specific challenges you encountered during model implementation, such as data inconsistencies or integration issues. Emphasize your problem-solving strategies and how you overcame these challenges to successfully implement the models.

Discuss techniques you use to ensure model accuracy, such as backtesting, peer reviews, and implementing benchmarks. Emphasize the importance of continuous improvement and staying updated with industry standards in risk modeling.

Prepare a specific example illustrating how you provided quantitative support to a trader or a risk manager. Highlight the analysis conducted, tools you used, and the impact your support had on trading decisions.

Share what drives your interest in risk modeling, such as the analytical nature of the work, the opportunity for innovation in financial products, and your desire to contribute to risk management in finance. Reflect on how your passion aligns with ING's goals.