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About the Role

The Risk division has the fundamental responsibility to protect the Bank. With group-wide responsibility for the management and control of credit, market, operational and reputational risks, we have a unique vantage point, which allows us a holistic view of our businesses and our clients. Nearly 4,000 employees work together to achieve our ambition to be an industry-leading risk management organisation. The Risk Methodology (RM) division is instrumental in developing and managing Deutsche Bank’s risk valuation methodologies, thereby providing risk managers with fit-for-purpose tools when it comes to allocating resources, managing risk appetite and making well-judged credit decisions. In addition, Risk Methodology ensures that all models developed within the division fulfil requirements relating to regulatory and economic capital calculations. Within RM, LGD/CCF Methodology team is primarily responsible for the calibration of Loss-Given-Default (LGD) and Credit Conversion Factors (CCF) parameters across all credit portfolios of Deutsche Bank Group. You will work in an environment that encourages an open communication, provides a mature feedback culture and offers employees a wide range of options to balance the requirements of the workplace with their personal and family needs.

Responsibilities

Development, calibration and maintenance of rating methodologies for the credit risk parameters for both retail and wholesale portfolios of the Deutsche Bank.
Implementation of EBA requirements and other existing and upcoming regulations to modelling of IRB-A credit risk parameters (CRR, EBA GL to PD/LGD, ECB guide to internal models, Basel III/IV, etc.).
Resolution of regulatory and internal findings related to the methodology of credit risk parameters or related models.
Efficient processing of large datasets for the purpose of model development or related statistical analyses.
In-depth analysis of the underlying data, identification of data deficiencies and addressing them.
Extensive data and statistical analyses for quantifying credit risk and decision-making.

Requirements

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.
Practical knowledge of the modeling of credit risk parameters (PD, LGD, CCF).
Strong IT / data management skills and advanced experience with relevant statistical software packages (SAS, Python) with ability to process and structure large amount of data.
Strong analytical skills and ability to solve problems efficiently in a self-reliant independent manner as well as a part of a large team.
Ability to work efficiently and professionally under tight timelines, provide structured results on a short notice or/and under stressful circumstances.
Excellent written and verbal skills in English.

Skills

SAS
Python
Credit Risk Modeling
Data Management
Statistical Analysis

Work Type

Full-time
Part-time

Education Level

Master's degree
PhD

Benefits

Consultation in difficult life situations
Mental health awareness trainings
Health check-ups
Vaccination drives
Advice on healthy living and nutrition
PME family service
FitnessCenter Job
Flexible working (e.g parttime, hybrid working, job tandem)
Pension plans
Banking services
Company bicycle
Deutschlandticket

About the Company

For over 150 years, our dedication to being the Global Hausbank for our clients has been driven by our people – in around 60 countries and across more than 150 nationalities. Their deep understanding, insights, expertise, and passion help our clients navigate an increasingly complex world – be it in our Corporate Bank, our Private Bank, our Investment Bank or our Asset Management (DWS) division. Together we can make a great impact for our clients at home and abroad, securing their lasting success and financial security. More information at: Deutsche Bank Careers (db.com)

Equal Opportunity

We welcome applications from all people and promote a positive, fair and inclusive work environment.