2026/Q1 - Senior Quantitative Modeller [Closed]

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.

#J-18808-Ljbffr

Full job description from WhatJobs. Apply for this role →