Senior Expert Credit Risk Management (IFRS 9 & Economic Capital) (m/w/d)
emagine Polska
⚲ Stuttgart
Wymagania
- VBA
- Testing
- Governance
- Advisory
- Documentation
- Microsoft Excel
- Risk Management
- Credit Risk
- Python
- maintenance
Opis stanowiska
Framework conditions Start: May/June 2026 Location: Remote und Stuttgart Project duration: 7-10 months with option for extension Workload: 100% full‑time Responsibilities: • Further development, enhancement, and maintenance of internal PD, LGD and Forward‑Looking / Future Expectation models used for IFRS 9 Credit Risk Impairment and Economic Capital. • Design, implementation and methodological refinement of quantitative credit risk models, including portfolio‑specific calibrations and parameterizations. • Preparation of audit‑proof model documentation, covering methodology, assumptions, limitations, validation results and governance aspects. • Further development of methodological standards, best practices and internal guidelines for credit risk modelling and validation. • Knowledge transfer and advisory support to internal stakeholders on complex quantitative and regulatory topics. Professional Qualifications • Advanced academic degree (Master’s or PhD) in Quantitative Finance, Mathematics, Econometrics, Statistics or a comparable field. • Several years of professional experience as a senior quantitative expert in credit risk modelling, validation or risk methodology. • Deep practical knowledge of IFRS 9 ECL methodologies, including PD, LGD, EAD and forward‑looking adjustments. • Strong understanding of Economic Capital / portfolio credit risk models and their regulatory and managerial use. • Proven experience in model validation, testing frameworks and audit‑ready documentation. • Excellent command of quantitative methods (statistics, econometrics, time series, regression‑based and structural credit models). • Hands‑on experience with Python, SAS and Excel/VBA for model development, testing and analysis. • Familiarity with banking risk systems and data environments (e.g. PD/LGD engines, portfolio tools, data warehouses). • Ability to explain complex quantitative topics clearly to non‑technical stakeholders, auditors and management. • Very good written and spoken German and English; ability to work confidently in an international environment.