Location
London

Hours
Full Time

Salary
Competitive, commensurate with experience

About the Role
Join a team at the forefront of quantitative model review and governance within one of the world's leading financial institutions. This role offers the 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 will 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 will 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. The team conducts 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. Working closely with valuation control, trading, finance, market risk, technology, and other control functions, you will use modern analytical and automation tools to enhance review quality and efficiency.

Key responsibilities include evaluating the conceptual soundness of model and qualitative methodology specifications, assessing valuation and risk measurement methodologies, designing targeted independent tests using Python and data analysis, reviewing derivatives valuation and risk methodologies, assessing statistical and machine learning approaches, reviewing implementation and data lineage, leveraging AI and automation tools responsibly, documenting findings clearly, representing the team in governance and regulatory interactions, supporting model governance activities, and contributing to the development of reusable tools and governance practices.

You will maintain awareness of industry developments, regulatory expectations, and market practices to ensure the firm’s model risk governance remains best-in-class.

Experience
- 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.
- Experience in model validation, quantitative research, model development, valuation control, market risk, product control, trading analytics, or a related control function is preferred.
- Knowledge of Corporate & Investment Banking trading asset classes such as Rates, Foreign Exchange, Equities, Credit, Commodities, or structured products is advantageous.
- Familiarity with Monte Carlo simulation, finite difference or PDE methods, curve construction, volatility surface modelling, regression, clustering, optimisation, machine learning, or model performance monitoring is desirable.
- 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.

About you
- Strong analytical judgement with the ability to challenge assumptions, assess materiality, and draw conclusions from incomplete evidence.
- Excellent written and verbal communication skills, able to explain technical concepts clearly to both quantitative and non-quantitative stakeholders.
- Inquisitive and evidence-driven mindset, confident in asking challenging questions and defending 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.

Qualifications
- Degree or equivalent qualification in a quantitative discipline such as mathematical finance, statistics, applied mathematics, physics, engineering, or computer science.
- Practical programming skills in Python or similar languages.
- Commitment to continuous learning and staying current with industry and regulatory developments.