Analyst, Quantitative Market Risk

Analyst - Quantitative RiskLondon

This is a quantitative role sitting within Risk Management, focused on the design, implementation and validation of traded-risk models that support market risk, counterparty exposure and capital across multiple asset classes.

Analyst - Quantitative RiskLondon

We are working with a global bank to hire an Analyst into its Risk & Analytics Modelling team in London. This is a quantitative role sitting within Risk Management, focused on the design, implementation and validation of traded-risk models that support market risk, counterparty exposure and capital across multiple asset classes.

You will join a small, technical team responsible for:

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  Developing, enhancing and maintaining risk and exposure models used for trading-book portfolios (e.g. VaR, sensitivities, stress testing, counterparty exposure metrics).

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  Supporting model validation through independent testing, benchmarking and performance analysis.

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  Working with large market-data and trade-data sets to build and maintain time series and risk-factor representations (rates, FX, credit, equities, commodities).

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  Producing clear analysis and documentation of model behaviour, assumptions, limitations and monitoring results for risk committees and senior stakeholders.

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  Collaborating with Market Risk, Front Office, Model Risk and IT to implement model changes and ensure accurate, timely risk measurement.

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The role offers a broad view across products and desks, with day-to-day work that is genuinely modelling- and analytics-focused rather than pure reporting.

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  Strong quantitative academic background, typically in a numerate discipline such as Mathematics, Statistics, Physics, Engineering, Economics/Finance with significant quantitative content.

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  Practical experience (internship or full-time) in one or more of: market risk, model validation, quantitative risk, pricing models, or traded-products analytics.

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  Good working knowledge of financial markets and products, especially derivatives (options, swaps, forwards) and core risk concepts (VaR, greeks, stress testing).

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  Programming ability in Python (or similar language), comfortable with data-handling and statistical libraries, and willing to develop this further.

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If interested, please apply or send a copy of your CV to

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