2026/Q1 - Senior Quantitative Modeller [Closed]

Allocation Strategy Ltd.; Greater London; Hybrid; GBP 90,000 - 130,000; Full time

Benefits offered by this job

Equity participation

Hybrid work model

International exposure

Access to advanced technology

Job summary

Allocation Strategy Ltd. is seeking a Senior Quantitative Modeller to architect, build, and evolve its core modelling and analytics platform for institutional asset allocation. You will own models and systems end-to-end in a fintech environment, collaborating closely with founders and senior teams.

You will design production-grade models for asset allocation and risk, develop AI-assisted workflows, and extend data pipelines and cloud-based workflows to scale with data complexity and client needs.

Qualifications

• Master's or PhD in a quantitative discipline or equivalent experience.
• 5+ years in quantitative modelling, software engineering, or applied research.
• Expert-level Python experience with numerical, statistical, or ML libraries.
• Experience building and operating backend systems and data pipelines in a cloud environment.
• Experience validating, testing, and deploying quantitative or ML models.

Responsibilities

• Architect, build, and evolve Allocation Strategy's core modelling and analytics platform.
• Implement, validate, and productionise advanced models for asset allocation, risk, macro and scenario analysis.
• Develop AI-assisted research and modelling workflows, including data engineering, model design, evaluation, and monitoring.
• Translate research and investment logic into efficient, testable code.
• Prototype new modelling approaches and analytical tools, then productionise them.
• Build and maintain backend systems, data pipelines, and APIs for research and client applications.
• Design and operate cloud-based data and model workflows, including orchestration and monitoring.
• Contribute to system architecture, performance optimisation, and scalability.

Skills

Analytical mindset

Strong communication

Autonomous work

Team collaboration

Education

Master's degree in quantitative field

PhD preferred

Tools

Python

NumPy

pandas

PyTorch

JAX

TensorFlow

AWS

GCP

Azure

Job description

We're looking for a Senior Quantitative Modeller to architect, build, and evolve our core modelling and analytics platform. This is a rare opportunity to join a fintech redefining institutional asset allocation at an early stage, with hands‑on ownership of the models and systems that power everything we do.

About Us

Allocation Strategy is a London-based fintech providing analytical infrastructure to institutional investors. Our mission is to set the industry standard in asset allocation analytics - transforming how investors make their most important portfolio decisions. Our subscription-based solutions combine cutting‑edge analytics with efficiency, helping clients do more with less.

What You Will Do

• Work directly with the Heads of Technology and Research to architect, build, and evolve Allocation Strategy's core modelling and analytics platform.
• Implement, validate, and productionise advanced models for asset allocation, risk, macro and scenario analysis, including data preparation, testing, calibration, optimisation, and maintenance as models and data evolve.
• Develop AI‑assisted research and modelling workflows, including data engineering, model design, evaluation, and monitoring.
• Translate theoretical research and investment logic into efficient, testable, and maintainable code.
• Rapidly prototype new modelling approaches and analytical tools, then harden them for production use.
• Build and maintain robust backend systems, data pipelines, and APIs supporting both internal research and client‑facing applications.
• Design, operate, and evolve cloud‑based data and model workflows, including orchestration, scheduling, monitoring, and failure handling.
• Contribute to system architecture, performance optimisation, and scalability as the platform and dataset complexity grow.
• Establish and uphold high engineering and research standards, including testing, documentation, and reproducibility.
• Collaborate closely with product and research stakeholders to ensure models are usable, interpretable, and commercially relevant.

Qualifications

• Master's or PhD degree in a quantitative discipline (or equivalent professional experience).
• 5+ years of relevant professional experience in quantitative modelling, software engineering, or applied research.
• Strong software engineering skills, with a track record of building and maintaining production‑quality systems.
• Expert‑level Python experience with numerical, statistical, or ML libraries (e.g. NumPy, pandas, PyTorch, JAX, TensorFlow).
• Deep understanding of statistical modelling, optimisation, or machine‑learning techniques.
• Experience building and operating backend systems and data pipelines in a cloud environment (e.g. AWS, GCP, or Azure).
• Experience validating, testing, and deploying quantitative or ML models.
• Comfortable working autonomously in a small, senior team, partnering closely with Founders.
• Strong analytical judgement, communication skills, and attention to detail.
• Experience with designing and refining large scale dynamic models.
• Experience applying AI or ML methods to real‑world, noisy financial or economic data.
• Strong awareness of the investment industry landscape, financial instruments, and market / economic events and news flow.
• Familiarity with finance and asset pricing theory and empirical methods, and the application of these concepts in the investment industry.
• Familiarity with cloud infrastructure, containerisation, orchestration, and CI/CD for model deployment.
• Experience in building institutional‑grade analytical tools or dashboards for sophisticated end users.
• Prior experience in a startup or early‑stage technology environment.

What we offer

Compensation

• Equity participation in a high‑growth venture
• Competitive base salary.

Other Benefits

• A collaborative, mission‑driven environment where your work directly shapes how institutional investors make multi‑billion‑dollar decisions
• Rapid career progression as the company scales
• Hybrid working model with international exposure
• Access to advanced technology and resources.