Regulatory Reporting & Analysis Assistant Manager

Job Description

Responsibilities

• Perform accurate and timely calculation of Counterparty Credit Risk (CCR), Leverage and Settlement Risk exposures and RWAs – including the effective use of the Moody’s Ray calculator.
• Produce and validate daily Leverage and monthly RWA and Leverage Returns across derivatives and SFT portfolios.
• Analyse period on period movements, trends, identify anomalies, and provide commentary to team managers.
• Support regulatory and internal reporting requirements.
• Assist managers in the calculation, reporting and analysis of capital to support New Products and Strategic Transactions.
• Maintain effective control frameworks to ensure robust outputs.
• Build and maintain SQL/Python scripts for data extraction, transformation, and analysis to drive and support Finance data transformation.
• Build and enhance Power BI dashboards to deliver intuitive and interactive MI to internal customers.
• Utilise Power Apps to improve MI, Checks and Analysis.
• Collaborate with IT specialists and our core analysis team and our Data leads to improve data quality and ensure data integrity.
• Find opportunities for automation and process improvement across reporting workflows.
• Work closely with Risk, Finance, and business teams to understand reporting needs and deliver actionable insights.
• Present findings and recommendations to managers.

Requirements

• Strong finance background and experience required, at least part-qualified and currently studying for exams.
• Minimum 1 year of experience applying and understanding RWA rules and calculations, including interpreting PRA frameworks (such as UK CRR/Basel 3.1, EMIR) across Credit Risk, Securitisations, and Counterparty Credit Risk, or at least 1 year of experience applying statutory accounting standards such as IFRS.
• Background experience in Financial Services or trained with a large accountancy practice is advantageous.
• Data Analytics: Proficient in excel for data manipulation, analysis, and automation.
• Hands on experience with SQL and/or Python, or a clear enthusiasm for learning and building capability in these tools.
• Visualisation: Power BI skills for dashboard creation and MI delivery.
• Data Management: Experience with SQL, data warehousing, and ETL processes.