Credit Risk Senior Associate

N26 is looking for a Credit Risk Senior Associate to join N26's Retail Mortgage team. The core purpose is to design, implement, and manage robust data analytics and second-line process controls for the mortgage portfolio. The role emphasizes deep methodological expertise, strong SQL and Python skills, and a proactive curiosity for broader mortgage business aspects, including macroeconomic analysis of collateral and digital process controls. The Senior Associate will ensure rigorous regulatory compliance (Dutch, EU, German, especially MaRisk) and contribute to scaling the credit risk function through data-driven insights and control effectiveness.

**In this role you will**

- Contribute significantly to the further development of N26's mortgage credit risk function, aligning with N26's growth aspirations, robust risk management objectives, and stringent regulatory compliance requirements within the retail mortgage business.

- Play a key role in the continuous enhancement of N26's global mortgage governance framework, policies, and procedures, ensuring full alignment with the latest Dutch (e.g., THRK), European (e.g., EBA GL LOM), and German (MaRisk, KWG) regulations.

- Support the further development and seamless implementation of end-to-end mortgage credit processes and criteria. This includes, but is not limited to, loan granting, comprehensive collateral management, sophisticated monitoring, proactive early warning systems, intensified and problem loan management, and accurate loan loss provisioning.

- Design, implement, and operate robust second-line control frameworks and tools for mortgage processes and the portfolio, including for the oversight of business activities and effective monitoring of third-party service providers.

- Develop and maintain a resilient and accurate mortgage credit risk database, crucial for precise portfolio and single case monitoring, portfolio reporting, and loan loss provisioning, with a strong focus on data quality and integrity.

- Conduct in-depth data analysis and support further development of quantitative models (PD, LGD) to assess key risk indicators across obligor, collateral, and portfolio levels within the mortgage domain.

- Proactively run comprehensive risk analyses, including assessing the impact of macroeconomic factors on collateral values and broader portfolio performance.

- Partner with Mortgage Business, Group Treasury, Capital Markets, Corporate Finance, Risk Controlling, Accounting, Regulatory Reporting, and Tech departments to implement credit requirements, help ensure transparency, and compliance with applicable credit law and regulations, and contribute to establishing a risk culture in the organization.

**Background**

- Bachelor's degree in finance, economics, mathematics, computer science, or a comparable quantitative field; an additional qualification (e.g., Master's degree in a relevant field, passed CFA or FRM exams) is a strong plus.

- 3+ years of experience in credit risk management, particularly with a focus on retail mortgage products, data analytics, process controls, or credit risk methodology development. Previous experience in a FinTech environment is a plus.

**Skills**

- Good understanding of key risk indicators across obligor, collateral, and portfolio levels within the mortgage domain.

- Solid understanding of processes across the entire mortgage value chain (e.g., credit decisioning, monitoring, early warning, intensified and problem loan management).

- Solid regulatory knowledge of Dutch (e.g., THRK), European (e.g., EBA GL LOM), and German (MaRisk, KWG) regulations; successful track record of understanding their implementation and liaising with supervisory authorities is a strong plus.

- Proven experience in building, implementing, and running credit process controls and oversight frameworks.

- Strong proficiency in SQL for data extraction, manipulation, and analysis; experience with other programming languages like Python for quantitative analysis and model development is a significant advantage.

- Solid knowledge of credit risk methodology for mortgages, including PD/LGD models, debt-servicing ability, and advanced collateral valuation techniques, with a keen understanding of integrating ESG factors.

- Strong analytical and quantitative skills, with the ability to independently generate actionable insights from complex data.

- Experience with data governance and data quality management processes is a strong plus.

- Fluent English (German and/or Dutch is a strong plus).

**Traits**

- Curiosity and Hands-On Approach: An inherent curiosity about the underlying mechanics of the mortgage business, macroeconomic factors impacting collateral values, and a strong hands-on attitude towards problem-solving.

- Analytical Rigor & Attention to Detail: Possessing a meticulous attention to detail coupled with exceptional analytical and problem-solving skills.

- Proactive Drive for Improvement: A strong drive to challenge ex