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Senior Quantitative Analyst
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Quantitative Analyst – Quantitative Risk
London | Hybrid
Up to £115,000 base + strong bonus + benefits
We are working with a leading global asset manager looking to hire a Quantitative Analyst into a small, highly technical team responsible for quantitative model validation globally across the firm.
This is not a traditional model validation role centred around governance, documentation or prescribed testing. The team operates as an independent quantitative function within Risk, working closely with investment teams and providing challenge across a remarkably broad range of models.
The remit spans investment and portfolio models, risk models, pricing models, ESG and increasingly AI and machine learning, giving you exposure to quantitative problems across the investment business rather than specialising in a single model type.
The role
You will independently assess and challenge quantitative models used across the organisation. A typical piece of work can involve getting into the underlying mathematics and assumptions, rebuilding a model independently, conducting your own quantitative analysis and using the results to challenge the existing methodology.
You will have significant autonomy over how you approach each problem and will be expected not only to identify weaknesses, but also to propose improvements and alternative approaches. Alongside model validation, there is scope to contribute directly to the development, enhancement and implementation of quantitative risk models, as well as building analytical tooling and automation for the team.
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The role is highly stakeholder-facing. You will work directly with model owners, quantitative teams and investment professionals, so you need to be able to explain complex quantitative conclusions clearly and confidently challenge senior stakeholders when required.
What they're looking for
The team is deliberately looking for strong, intellectually curious generalist quants rather than career model-validation specialists.
Previous model validation experience is not required. Relevant backgrounds could include quantitative research, front-office quant, investment risk, systematic investing, quantitative development or other mathematically rigorous roles.
You'll ideally bring:
- Strong mathematical and statistical foundations, with the ability to understand and challenge models at a fundamental level.
- Hands-on experience developing, analysing or implementing quantitative models.
- Strong programming skills, ideally Python.
- Broad intellectual curiosity and an interest in tackling very different quantitative problems.
- The communication skills to challenge model owners and investment professionals credibly.
- A strong quantitative academic background and/or substantial commercial quantitative experience.
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Why consider it?
The biggest differentiator is breadth. Rather than spending your career focused on one model family or asset class, you'll encounter quantitative problems from across a global asset manager.
You'll remain close to the investment business while gaining exposure to areas ranging from portfolio construction and investment risk through to pricing and emerging AI/ML model risk.
It's also an interesting move for front-office or investment quants who enjoy the technical and intellectual side of their work but want greater variety and a more sustainable working environment (hybrid working, 9-5), without moving away from genuinely challenging quantitative problems. The team is deliberately small, giving individuals significant ownership, visibility and autonomy.
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