Job Title: Counterparty Credit Risk Methodology Strat

Location: Mumbai, India

Corporate Title: Associate

Role Description:

- You will be joining Group Strategic Analytics (Strats), which combines expertise in quantitative analytics, modelling, pricing and risk management with deep understanding of system architecture and programming.

- Within GSA, the Counterparty Credit Risk Methodology team is responsible for Deutsche Bank's derivatives exposure engine to simulate exposure profiles for derivatives and securities financing transactions by applying regulatory approved simulation models.

- The profiles are simulated via Monte Carlo and are the basis to calculate exposure metrics such as EPE (Expected Positive Exposure), PFE (Potential Future Exposure) and AEE (Average Expected Exposure) entering the Economic and Regulatory capital calculations for Counterparty Credit Risk. The team also works closely with Market Risk Management on Basel III projects such as FRTB CVA (Credit Valuation Adjustment) and Prudential Valuation adjustment on XVA.

Your key responsibilities:

- Develop, support and enhance Backtesting, Risk-Not-Covered in IMM (RNIEE) and other tools to monitor the performance of the Counterparty Credit Risk models..

- Design, build, and maintain analytical tools and scripts, ensuring all code/documentation is maintained within the Kannon repository and compliant with internal governance.

- Produce high-quality quarterly Backtesting and RNIEE reports for senior management, providing clear explanations of results, drivers, and methodological updates.

- Respond to stakeholder and management queries, providing clear, data- driven explanations of results, assumptions, and methodology choices.

- Support efforts around internal and external audit response including addressing queries and producing ad hoc analysis.

- Drive the timely closure of assigned regulatory/audit/validation findings.

- Provide expertise/support to our main stakeholder in Credit Risk Management, Front Office, Finance and Technology.

Your skills and experience:

- Strong educational background in Quantitative discipline such as Engineering, Financial maths, Statistics etc preferably from good colleges in India e.g. IIT, NIT, ISI etc.

- Demonstrable relevant 3-5 years industry experience in a similar role with an investment bank or financial institution. Familiarity with Counterparty risk will be preferred.

- Good background in financial maths, statistics, and familiarity with a mainstream programming language preferably Python.

- Good knowledge of financial instruments/derivatives and markets across all asset classes.

- Good computing and programming (coding) skills and experience, utilising programming languages such as Python, SQL etc.

- Hands-on experience with Bitbucket, including creating, maintaining, and managing code repositories.

- Strong analytical mindset with excellent problem solving and data interpretation skills.

- Excellent communication and interpersonal skills, as projects can require interaction and synchronisation with other teams.

- Highly organized and can work both independently and as part of a team in a fast-paced environment.