01Overview
We are in need for an IMA Quant Analyst to support a market risk function responsible for the development, monitoring and validation of Internal Model Approach (IMA) models under the Fundamental Review of the Trading Book (FRTB). The role is suited to candidates seeking either a permanent position or a contract engagement.
Who We Are Looking For
Quanteam UK are looking for a quantitatively minded analyst to contribute to the following areas:
Contributing to the design, development and enhancement of IMA models used for regulatory capital calculation, including Value-at-Risk (VaR), Expected Shortfall (ES) and Stressed Expected Shortfall (SES).Performing ongoing model monitoring, including backtesting and Profit and Loss Attribution (PLA) testing, to confirm that models continue to meet regulatory eligibility tests.Investigating backtesting exceptions and PLA test breaches, working with trading, risk and technology colleagues to identify root causes and remediate them.Supporting model validation and documentation, ensuring models meet internal governance standards and regulatory expectations.Assisting with regulatory submissions and responding to queries raised by internal risk committees and regulators.Liaising with front office, market risk and technology stakeholders to understand product and process changes and assess their impact on IMA models.Contributing to the ongoing development of risk methodology, data quality and process automation.
Technical Competence
A degree in a quantitative discipline, such as Mathematics, Physics, Engineering or Computer Science; a postgraduate qualification is beneficial.A sound understanding of market risk methodologies, including VaR, Expected Shortfall, backtesting and Profit and Loss Attribution.Working knowledge of the FRTB regulatory framework and Internal Model Approach requirements.Proficiency in Python; experience with C++ or another object-oriented language is advantageous.Competence in SQL and experience working with large, complex datasets.A solid grounding in statistics and probability theory as applied to financial markets.
Behavioural Competence
Strong analytical and problem-solving skills, with the ability to investigate complex issues methodically.Clear written and verbal communication, with the ability to explain technical concepts to non-technical stakeholders.Comfortable working independently and prioritising a varied workload against reporting deadlines.A collaborative approach, able to work effectively with risk, trading and technology colleagues.Diligence and attention to detail, particularly with regard to regulatory documentation and reporting. .
