Risk Methodology Specialist

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.

In an increasingly complex environment, risk management is fast becoming the most sought after place to build a career within the banking world. Risk at Deutsche Bank is relied upon to help shape the strategy of the organisation and the wider industry agenda.

**Risk Methodology (RM) **develops and manages the risk valuation methodologies for Deutsche Bank. The models, methodologies and tools developed in RM are utilized by Risk Managers for the efficient resource allocation, managing the risk appetite and credit decisions in the day to day business process. In addition, RM ensures that the models fulfill the regulatory requirements with regard to regulatory and economic capital calculations.

Split in various sub teams, the Berlin team provides methodology expertise & operational leverage to market risk managers located in New York, London, Frankfurt and Asia. In addition, the team contributes to the model development and implementation of these models.

Within Risk Methodology, the Treasury Modeling and Analytics (TMA) team partners with the Treasury and Finance organizations to provide modeling and analytical problem solving for important regulatory and internal strategic initiatives - such as Capital Stress Testing, Risk in the Banking Book, and Strategic Planning.

The role holder will have the opportunity to gain a fundamental understanding of the Bank’s risk and capital processes including model projection methodology across B/PPNR, credit risk, market risk, operational risk, and RWA as well as an enterprise-level perspective of CCAR, Interest Rate Risk, and Strategic Planning activities.

You will work in a central role within an evolving discipline and find 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.

**Your key responsibilities**
- Very complex analysis, evaluation & decision-making. Contribute to model development engagement with the lines of business and contribute to representing RM in model development activities with the wide variety of model stakeholders from General Technology to Treasury, Finance, and Line of Business leadership; therein develop and implementation of Board-level modeling analytics and execute on model development protocols
- Data processing: Collect very complex information and process it ready for decision-making. Check feasibility of implementation approaches with Information Technology and Operations and identify the most viable option for modeling work within the TMA modeling infrastructure. The modeling infrastructure is Deutsche Bank’s strategic model development and execution platform that is comprised of three components: an R code library that caters to both modelling and analytical requirements, an Oracle database, and an R-Shiny based reporting layer
- Improvements: Development of very complex methods, processes or analyses as well as improvements. Propose advances in model design and data analysis and benchmark DB’s approach against industry best practice and drive applicable improvements.
- Relationship management, Communicate effectively and regularly with Senior Management and build relationships in close interaction with DB leaders and executives, as well as senior members from the various lines of business, Treasury, Finance, Risk, Model Risk Management.
- Managerial Responsibility, Transfer of specialist know-how to employees: assisting more junior modeling teams with the model development narrative about how to communicate key modeling decisions

**Your skills and experiences**
- Education and Experience:

- Relevant university degree (Master or PhD) in a quantitative discipline with a programming concentration (e.g., Economics, computer science, applied statistics / mathematics, engineering, operations research, etc.) and relevant professional experience necessary ideally in a coding and modeling discipline.

**Competencies: Particular methodological expertise necessary**
- Very strong quantitative background, extensive analytical skills and ability to efficiently solve problems independently and proactively.
- Extensive experience with B/PPNR projections models and CCAR concerning e.g. the following model classes: linear and/or non-linear generalized linear mixed models, PCS & Factor analysis, state space models, panel data analysis, account-level logistic, decision tree and cohorting analysis
- Knowledge of Deposit, Loan, Treasury, ALM, Liquidity, and Interest Rate Risk p