<p>A Model Risk Analyst ensures the soundness, reliability and governance of quantitative models used across a financial institution. The role combines technical modelling skills with risk assessment and regulatory knowledge to protect the organisation from model related losses and compliance breaches.</p>
<p>This job description outlines the profile, core responsibilities and required qualifications for a Model Risk Analyst. It is intended for HR professionals, recruiters and staffing agencies seeking a candidate who can validate, monitor and improve financial models while embedding robust model governance practices.</p>
<h2>Model Risk Analyst Job Profile</h2>
<p>The Model Risk Analyst supports the model lifecycle through validation, independent review and ongoing performance monitoring. They liaise with model owners, risk teams and regulators to ensure models are fit for purpose and documented to firm standards.</p>
<p>Key activities include model validation, backtesting, sensitivity analysis and reporting. The role demands strong quantitative skills, attention to detail and the ability to communicate technical findings to non technical stakeholders.</p>
<h2>Model Risk Analyst Job Description</h2>
<p>The Model Risk Analyst is responsible for assessing the conceptual soundness, implementation quality and empirical performance of credit, market, capital and operational risk models. They design validation frameworks, execute independent tests, and challenge assumptions or data inputs used in models. The role contributes to the development of model risk policies and the maintenance of a central model inventory.</p>
<p>Day to day work involves running diagnostic analyses, performing statistical tests, preparing validation reports and presenting findings to senior risk committees. The analyst will also support model remediation activities and track outstanding issues to closure. Collaboration with model developers, data engineers and business units is essential to address model limitations and improve model controls.</p>
<p>The position requires familiarity with regulatory frameworks such as Basel, PRA expectations and internal model risk governance standards. Candidates must be comfortable working with large data sets, coding in languages such as Python or R, and using statistical techniques to quantify model uncertainty and potential biases.</p>
<h2>Model Risk Analyst Duties and Responsibilities</h2>
<ul>
<li>Perform independent model validations and reviews across credit, market and capital models.</li>
<li>Design and execute backtesting, stress testing and sensitivity analysis to assess model performance.</li>
<li>Evaluate model inputs, assumptions, data quality and implementation fidelity.</li>
<li>Prepare clear, concise validation reports with findings, recommendations and remediation plans.</li>
<li>Maintain and update the central model inventory and support model approval workflows.</li>
<li>Engage with model owners, developers and business stakeholders to discuss validation outcomes.</li>
<li>Support the development and improvement of model risk policies, standards and best practice.</li>
<li>Monitor model performance post implementation and report material exceptions to governance fora.</li>
<li>Provide quantitative support for regulatory submissions and internal audits related to models.</li>
<li>Stay current with regulatory expectations, industry practice and advances in statistical modelling.</li>
</ul>
<h2>Model Risk Analyst Requirements and Qualifications</h2>
<ul>
<li>Bachelor degree or higher in Mathematics, Statistics, Economics, Finance, Engineering or related quantitative discipline.</li>
<li>Proven experience in model validation, quantitative risk or risk analytics within banking or financial services.</li>
<li>Strong programming skills in Python, R, SAS or equivalent for data analysis and model testing.</li>
<li>Solid understanding of statistical methods, econometrics, time series analysis and machine learning techniques.</li>
<li>Familiarity with regulatory frameworks such as Basel II/III and PRA expectations for model risk.</li>
<li>Excellent written and verbal communication skills with the ability to explain technical issues to non technical audiences.</li>
<li>Attention to detail, strong analytical rigour and the capacity to work independently and in teams.</li>
<li>Experience with model governance, documentation standards and version control.</li>
<li>Professional qualifications such as CFA, FRM or equivalent are advantageous.</li>
<li>Ability to manage multiple priorities and meet tight deadlines in a controlled environment.</li>
</ul>