Market and Counterparty Credit Risk Manager

Description : The role is to provide technical market risk oversight of the trading business, and this includes both analysis and reporting on risk and risk capital (on daily and ad hoc basis). The team is small and very flat in structure, therefore the team is responsible for building their own Python-based analytic tools and reporting outputs, and the whole team delivers on work outputs. Perform BAU daily risk oversight (20% of the role) Proactively identify, quantify and monitor all risks for your assigned Desk on a daily basis. This includes investigating, assessing and reporting on the arising risks, and ensuring they are well understood by management. Ensure that you understand and are able to use the most appropriate risk methodologies and techniques to do so. Daily risk reports must be distributed to the business on a daily basis and in a timely manner. Reports should reflect the relevant risks and include value-add analysis that provides clear understanding of top risks. Ensure daily risk limit breaches, exceptions or technical issues are pro-actively dealt with and escalated as necessary Where existing risk reports require improvement or change, be able to design, develop and compile accurate and meaningful replacements that can be quickly generated with minimal manual intervention, using the risk calculation engine, Python and PowerBI (for reporting outputs), as is most appropriate for the specific requirements. Perform ad hoc risk analysis and other risk-related work (80% of the role) Design and develop accurate and meaningful analytic tools that will quickly generate provide risk insights or generate efficiency gains with minimal manual intervention, using the risk calculation engine (Chi) and Python. Recent examples, include the creation of a stress testing Python toolkit that generates and extracts scenario results from the risk engine Chi. Where required, you may be required to analyze risk across the whole Trading Book and therefore should ensure that you maintain a broad understanding of the different Desks and their respective markets. Investigate and explain changes in the Trading Book Regulatory Capital. Build any necessary Python-based tools to help in this process. Generate the associated external reporting templates for the Prudential Reporting Team. Monitor and explain changes in derivatives margin / collateral balances Monitor and explain changes in XVA reserves and sensitivities Where needed, understand and analyze the impact of new regulation on the trading businesses, as well as provide technical guidance on and validate the implementation of new regulatory rules. As part of your broader control framework responsibilities, you may be expected to: Develop and enhance market risk methodologies. When required, monitor and evaluate model assumptions to assess appropriateness. Challenge the appropriateness and usage of pricing models where necessary. Work with other teams to remediate and improve existing processes across other control functions, as required. Draft documentation to a high standard, including policy documents and requirements specifications. Where project requirements relate to regulatory implementations, your work will include reviewing the regulatory specifications and possibly providing interpretations. Pre-requisite technical knowledge An understanding of market risk management principles and practices is a pre-requisite Detailed, technical financial product knowledge across asset classes (including appropriate pricing models and risk methodologies). Knowledge of risk methodologies in general (for example Value at Risk, Backtesting, Stress Testing, Scenario Analysis) An understanding of numerical techniques employed within financial models, for example Monte Carlo, Finite Difference (including Bump & Revalue method), lattice methods, etc. Ability to code in Python is a must An ability to build and edit reports using PowerBI. Additional technical knowledge that would be beneficial but is not a pre-requisite: An understanding of market data factors and market risk sensitivities including under FRTB (delta, vega, curvature) TimeSeries Market Data – Missing Value Imputation (Proxying) and Outlier Treatment Fundamental understanding of counterparty credit risk (e.g., EPE metric) and XVA (CVA, FVA) would be a distinct advantage A good understanding of the trade lifecycle process would also be an advantage Knowledge of the broader bank regulatory landscape is an advantage, particularly relating to market risk, CVA risk and counterparty credit risk A strong understanding of the 3LoD model, and the necessary segregation of duties that are required Strong Excel knowledge is an advantage Strong capability to automate data extraction, transformation and manual reporting processes through Python-based solutions, improving efficiency, accuracy and scalability. Educational Background: A Bachelor's degree (or higher) in a Numerate discipline. This can be applied maths (such as engineering) or pure maths. Core skills and personal attributes Analytical and numerate. A problem solver. Diligent, with strong attention to detail A pro-active self-starter who takes initiative and has the commitment to follow projects to completion A hands-on, pragmatic approach towards work delivery. An ability to self-manage Willingness to learn and ability to pick up new skills and technologies An ability to think independently and challenge the status quo An ability to explain complex issues clearly. Be timely and always act in a professional manner