Credit Risk Modelling Quantitative Strategist

About the role: We are seeking experienced and motivated Credit Risk Modelling Strats, for our IRB Risk Methodology team, who will be responsible for the development and maintenance of the PD/LGD/CCF models for the Groups credit portfolios. In this role, you will engage extensively with a variety of stakeholders (e.g., Business Lending, Risk, Finance etc.) to build industry leading models which accurately reflect DBs risk profile and are compliant with various regulatory requirements. You will work in an environment that encourages open communication, focuses on your professional development, provides a mature feedback culture, and offers a wide range of options to balance the requirements of the workplace with their personal and family needs.

Your key responsibilities:

• Model development and management: Development, implementation, and maintenance of methodologies for the credit risk parameters for retail and wholesale portfolios of the Deutsche Bank compliant with regulatory requirements to modelling of credit risk parameters (CRR, EBA GL on PD/LGD, etc.)
• Regulatory remediation: Resolution of regulatory and internal findings related to the methodology of credit risk parameters or related models.
• Stakeholder engagement: Active interaction with various internal stakeholders from Business, Credit Risk Management, Finance, Capital management etc.

Your skills and experience:

• Educational background: Relevant university degree (Master or/and PhD) in a quantitative discipline (e.g. Mathematical Finance/Statistics/Econometrics) with focus on application of theoretical knowledge into practice.
• Risk management and modelling experience: Knowledge of Credit Risk Management and relevant regulatory requirements as well as proven experience in internal modelling for 3-5 years.
• Programming capabilities: Strong analytical skills, proven ability to handle and optimize processing of large datasets, proficiency with advanced statistical techniques as well as hands-on experience with analytical packages (at least SAS and Python).
• Stakeholder management skills: Proven experience in delivering complex model development projects in a cross-functional setup.
• Communication skills: Effective communication skills, the ability to share clear messages and explain complex ideas in an understandable way, excellent written and verbal skills in English.