2026/Q2 - Senior Quantitative Engineer

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Please note: applications for this position will close on 14 June 2026.

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We are looking for a Senior Quantitative Engineer to join Allocation Strategy's technology team.

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This is a hands‑on, early‑stage role at the intersection of software engineering, quantitative modelling, applied AI, and investment analytics. You will work closely with the company founders, including the Heads of Technology and Research, to design, build, and evolve the firm's core data, analytics, and modelling platform.

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The role spans full‑stack development, backend systems, cloud infrastructure, data pipelines, quantitative research workflows, and production modelling systems. You will help translate advanced macro‑finance and asset‑allocation research into reliable, scalable software used by institutional clients.

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As an early member of a small, senior team, you will work end‑to‑end across research, prototyping, data engineering, model implementation, production systems, and client‑facing applications. This is a high‑ownership role for someone who is comfortable contributing wherever needed in a fast‑moving startup environment.

What you will do\n

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• Work directly with the Heads of Technology and Research to architect, build, and evolve Allocation Strategy's core modelling, analytics, and client‑facing platform.
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• Contribute to the development and maintenance of the frontend platform, including dashboards, data visualisations, and component libraries, using React/Next.js.
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• Help develop and maintain backend services, APIs, databases, and data pipelines supporting internal research and client‑facing applications.
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• Contribute to implementing, validating, and productionising models for asset allocation, risk, macro analysis, scenario analysis, and portfolio analytics – translating theoretical research and investment logic into efficient, testable code.
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• Prepare, clean, analyse, and maintain financial and economic datasets used in modelling and analytics.
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• Prototype and help harden new modelling approaches, analytical tools, and platform features.
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• Work across the design and build of our internal AI layer, including LLM integrations, MCP servers, and agentic tooling, to automate research workflows and deliver analytical insights within the client‑facing platform.
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• Help with the evolution of our cloud infrastructure on GCP – spanning compute, orchestration, and databases – to ensure models and workflows run efficiently, securely, and reliably.
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• Contribute to improving system performance, reliability, scalability, and maintainability as the platform, models, and datasets grow.
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• Collaborate closely with product, research, and technology stakeholders to ensure models and tools are usable, interpretable, and commercially relevant.
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Essential\n

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• Master's or PhD degree in a quantitative discipline (or equivalent professional experience).
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• 5+ years of relevant professional experience in quantitative modelling, software engineering, or applied research.
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• Strong software engineering skills, with a track record of building and maintaining production‑quality systems.
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• Expert‑level Python experience with numerical, statistical, or ML libraries (e.g. NumPy, pandas, PyTorch, JAX, TensorFlow).
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• Deep understanding of statistical modelling, optimisation, or machine‑learning techniques.
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• Experience building and operating backend systems and data pipelines in a cloud environment (e.g. AWS, GCP, or Azure).
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• Experience validating, testing, and deploying quantitative or ML models.
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• Comfortable working with high ownership in a small, senior team, partnering closely with Founders.
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• Strong analytical judgement, communication skills, and attention to detail.
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Desired\n

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• Experience with designing and refining large scale dynamic models.
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• Experience applying AI or ML methods to real‑world, noisy financial or economic data.
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• Strong awareness of the investment industry landscape, financial instruments, and market / economic events and news flow.
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• Familiarity with finance and asset pricing theory and empirical methods, and the application of these concepts in the investment industry.
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• Familiarity with cloud infrastructure, containerisation, orchestration, and CI/CD for model deployment.
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• Experience in building institutional‑grade analytical tools or dashboards for sophisticated end users.
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• Prior experience in a startup or early‑stage technology environment.
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Compensation\n

We offer a competitive salary, equity participation, and direct influence over the firm’s core technology and research direction.

About Allocation Strategy\n

Allocation Strategy is a London‑based fintech building cutting‑edge analytics for institutional asset allocation. Founded by alumni of Norges Bank Investment Management, we work with pension funds, sovereign wealth funds, and reserve managers across multiple geographies.

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