Quant Model Risk Analyst/Associate - VCG in London

Description

Join a team at the forefront of quantitative model review and governance within one of the world's leading financial institutions.

This is an opportunity to apply your expertise in mathematical finance, statistics, data analysis, and programming to assess methodologies that influence valuation, risk management, and capital decisions.

You'll collaborate with experts across trading, finance, risk, and technology while developing deep insight into complex financial products and modelling techniques.

Your work will help ensure the firm's models are robust, well-governed, and fit for purpose.

As an Analyst/Associate in Model Risk Governance and Review's Valuation Control Group team, you perform independent reviews of valuation, risk, valuation adjustment, and prudent valuation methodologies used across the Corporate & Investment Bank.

Model Risk Governance and Review is a global team of modelling experts within the firm's Risk Management and Compliance organization.

We conduct independent model review and governance activities to help identify, measure, and mitigate model risk across the firm.

You will assess methodologies, challenge assumptions, evaluate evidence, and communicate technical conclusions that support effective risk management and governance.

You will work closely with valuation control, trading, finance, market risk, technology, and other control functions while using modern analytical and automation tools to enhance review quality and efficiency.

Job Responsibilities

• Evaluate the conceptual soundness of model and qualitative methodology specifications, including assumptions, mathematical structure, empirical evidence, limitations, and controls.
• Assess valuation, risk measurement, and valuation adjustment methodologies, including fair value, liquidity, concentration, close-out cost, market price uncertainty, future hedging cost, and prudent valuation approaches.
• Use Python and data analysis techniques to design targeted independent tests, including benchmark comparisons, sensitivity analysis, backtesting, threshold calibration, small-sample analysis, and materiality assessments.
• Review derivatives valuation and risk methodologies, including volatility dynamics, stochastic rates, jumps, correlation, curve construction, proxying, aggregation, and risk decomposition.
• Assess statistical, data science, and machine learning approaches where relevant, including calibration quality, feature engineering, validation metrics, explainability, and monitoring.
• Review implementation and data lineage, including upstream dependencies, market data, sensitivity generation, system flows, and downstream usage.
• Leverage approved AI and automation tools to accelerate evidence review, code understanding, data analysis, documentation drafting, and quality checks while maintaining independent judgement, confidentiality, and model risk standards.
• Document review findings clearly and communicate conclusions to model developers, valuation control, trading, finance, market risk, technology, senior management, auditors, and regulators.
• Represent the team in review meetings, governance discussions, and regulatory or audit interactions.
• Support model governance activities, including model inventory quality, issue tracking, ongoing performance monitoring outcomes, review planning, and the escalation of model risk issues.

Contribute to the development of reusable tools, diagnostics, review standards, and governance practices while maintaining awareness of industry developments, regulatory expectations, and market practices.

Required Qualifications, Capabilities, and Skills

• Strong quantitative background in mathematical finance, statistics, applied mathematics, physics, engineering, computer science, or a related discipline.
• Practical coding ability in Python or a comparable programming language, with experience using data analysis to investigate technical questions.
• Understanding of derivatives pricing, risk sensitivities, calibration, probability, statistics, and numerical methods, or the ability to develop this knowledge quickly.
• Strong analytical judgement, including the ability to challenge assumptions, assess materiality, and draw conclusions from incomplete evidence.
• Excellent written and verbal communication skills, with the ability to explain technical concepts clearly to both quantitative and non-quantitative stakeholders.
• Inquisitive and evidence-driven mindset, with the confidence to ask challenging questions and defend conclusions.
• Strong risk and control mindset, including appropriate handling of confidential information, documentation quality, governance, and escalation practices.

Ability to collaborate across teams and manage shifting priorities under review deadlines.

Preferred Qualifications, Capabilities, and Skills

• Experience in model validation, quantitative research, model development, valuation control, market risk, product control, trading analytics, or a related control function.
• Knowledge of one or more Corporate & Investment Banking trading asset classes, including Rates, Foreign Exchange, Equities, Credit, Commodities, or structured products.
• Experience with Monte Carlo simulation, finite difference or partial differential equation methods, curve construction, volatility surface modelling, regression, clustering, optimisation, machine learning, or model performance monitoring.
• Experience building reproducible quantitative analysis in Python, including data cleaning, visualization, statistical testing, benchmarking, and automation.
• Experience using AI-assisted development, code review, document analysis, or research tools productively and responsibly.
• Knowledge of valuation adjustments, prudent valuation, fair value hierarchy, future valuation adjustments, additional valuation adjustments, market price uncertainty, close-out costs, concentration and liquidity methodologies, or related regulatory requirements.
• Experience interacting with senior stakeholders, auditors, or regulators.