VP – Liquidity & Market Quantitative Model Risk

Barclay Simpson; Greater London; On-site; GBP 75,000 - 110,000; Full time

Job summary

Barclay Simpson is seeking a technically adept risk professional to join its Liquidity and Market Risk team in London with hybrid working (2 days in the office). The role focuses on stress testing, model ownership, validation-style testing and deeper analysis of model algorithms, code and data.

You will monitor and govern risk models, test assumptions, and develop benchmarking models. A strong technical and quantitative background in model risk, validation or governance is essential.

Qualifications

• Experience in model validation, model risk, or model governance.
• Strong SQL, Python and R skills with ability to analyse complex models.
• Ability to interrogate algorithms and data, and work with large datasets.
• Experience communicating technical conclusions to technical and non-technical audiences.

Responsibilities

• Perform daily, weekly, monthly and quarterly model monitoring and governance activities.
• Test model assumptions, parameters, algorithms and outputs.
• Stress test models using extreme scenarios to identify weaknesses.
• Develop benchmarking and challenger models to assess model performance.
• Maintain model documentation in line with model risk policy.
• Run liquidity stress tests and assess impact of new products and currencies.
• Extract, clean and analyse large datasets; improve code and automate processes.

Skills

Advanced SQL

Python

R

Model risk

Model validation

Model governance

Quantitative analysis

Large datasets

Code improvement

Stakeholder communication

Job description

London | Hybrid working (2 days per week in office)

A globally significant financial markets organisation is looking for a technically strong risk professional to join its Liquidity and Market Risk team.

This is not a traditional liquidity reporting role. It is a hands‑on position focused on stress testing, model ownership, validation‑style testing and detailed analysis of model algorithms, code and data.

The role would suit someone from a model risk, model validation, model governance or quantitative consulting background who enjoys getting into the technical detail.

The role

You will help manage and monitor a portfolio of critical risk models, ensuring they remain robust, reliable and compliant with internal model risk standards.

You will test model behaviour under extreme conditions, investigate unexpected outputs and develop benchmarking or challenger models. You will also conduct liquidity stress testing and assess the impact of new products, services, participants and currencies.

The team is open to new ideas, giving you the opportunity to improve existing models, strengthen analytical processes and introduce greater automation.

Key responsibilities

• Perform daily, weekly, monthly and quarterly model monitoring and governance activities.
• Test model assumptions, parameters, algorithms and outputs.
• Stress test models using extreme scenarios to identify weaknesses or unexpected behaviour.
• Develop benchmarking and challenger models.
• Maintain model documentation in line with model risk policy.
• Run daily and quarterly liquidity stress tests, including scenarios where participants fail to meet payment obligations.
• Analyse the impact of market, geopolitical and operational events.
• Assess the liquidity implications of proposed products, services and strategic initiatives.
• Compare expected outcomes against risk appetite and escalates material findings.
• Extract, clean and analyse large and complex datasets.
• Improve existing code, automate processes and support system or data migrations.
• Present technical conclusions clearly to senior stakeholders and regulators.

Candidate profile

You will need a strong technical and quantitative background, ideally gained within:

• Model risk or model validation.
• Model governance or model monitoring.
• Quantitative risk analytics.
• A Big Four or specialist consultancy.
• A bank, financial institution or financial market infrastructure provider.

Candidates from consulting are particularly relevant where they have worked on model validation or technically complex quantitative assignments.

A financial markets background is useful but not essential. The organisation is more interested in your ability to understand unfamiliar models, interrogate algorithms and work confidently with code and large datasets.

Traditional liquidity or market risk candidates may also be suitable, provided their experience has involved substantial technical analysis rather than primarily reporting and governance committees.

Essential skills

• Experience of model validation, model risk, model governance or quantitative model testing.
• Confidence analysing model methodologies, assumptions and behaviour.
• Advanced SQL, including complex queries.
• Strong Python skills.
• Experience using R for quantitative analysis.
• Ability to work with and improve an existing code base.
• Experience handling large datasets.
• Strong analytical, problem-solving and quality-control skills.
• Clear communication with both technical and non-technical stakeholders.