Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Quantitative Analyst – Asset Allocation & Portfolio Construction (Buy-Side)

Octavius Finance
London
1 year ago
Applications closed

Related Jobs

View all jobs

Data Scientist, Quantitative Strategies (Asset & Wealth Management)

Data Scientist, Quantitative Strategies (Asset & Wealth Management)

ESG Data Scientist

ESG Data Scientist

Data Scientist, Proprietary Research

Data Scientist - Placement Year

An exciting opportunity has arisen to join a leading quantitative team focused on developing advanced asset allocation models and portfolio construction algorithms. This team covers all major global fixed income markets, including credit, interest rate, and foreign exchange risk, working in close collaboration with portfolio managers, traders, and colleagues across risk management, structured finance, and application development.

 

Key Responsibilities:

  • Develop innovative analytical tools and strategies for asset allocation and portfolio construction.
  • Collaborate with portfolio and risk managers to gather requirements and deliver customized quantitative solutions.
  • Program as part of a quantitative development team, contributing to a library of advanced models.
  • Take on leadership responsibilities, including mentoring junior analysts and driving key projects.

 

Required Skills and Experience:

  • Advanced degree in a quantitative discipline (PhD preferred) such as mathematics, finance, engineering, or a related field.
  • Minimum of 10 years of experience in quantitative research, preferably in fixed income on the buy-side.
  • Strong expertise in statistical techniques, including PCA, optimization methods (linear, quadratic, mixed integer), regression models, and practical machine learning applications.
  • Extensive knowledge of asset allocation methodologies, including mean-variance optimization, scenario-based models, robust allocation techniques, and Black-Litterman frameworks.
  • Proficiency in portfolio construction techniques across macro, sector, and security levels.
  • Programming expertise in Python, C++, and/or Java.
  • Additional experience in structured finance, credit modeling, or Monte Carlo simulations is a plus.
  • Proven ability to lead independent research and work effectively within a collaborative team environment.
  • Excellent communication and presentation skills to convey complex ideas clearly.

 

Apply to

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

AI Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we head into 2026, the AI hiring market in the UK is going through one of its biggest shake-ups yet. Economic conditions are still tight, some employers are cutting headcount, & AI itself is automating whole chunks of work. At the same time, demand for strong AI talent is still rising, salaries for in-demand skills remain high, & new roles are emerging around AI safety, governance & automation. Whether you are an AI job seeker planning your next move or a recruiter trying to build teams in a volatile market, understanding the key AI hiring trends for 2026 will help you stay ahead. This guide breaks down the most important trends to watch, what they mean in practice, & how to adapt – with practical actions for both candidates & hiring teams.

How to Write an AI CV that Beats ATS (UK examples)

Writing an AI CV for the UK market is about clarity, credibility, and alignment. Recruiters spend seconds scanning the top third of your CV, while Applicant Tracking Systems (ATS) check for relevant skills & recent impact. Your goal is to make both happy without gimmicks: plain structure, sharp evidence, and links that prove you can ship to production. This guide shows you exactly how to do that. You’ll get a clean CV anatomy, a phrase bank for measurable bullets, GitHub & portfolio tips, and three copy-ready UK examples (junior, mid, research). Paste the structure, replace the details, and tailor to each job ad.

AI Recruitment Trends 2025 (UK): What Job Seekers Must Know About Today’s Hiring Process

Summary: UK AI hiring has shifted from titles & puzzle rounds to skills, portfolios, evals, safety, governance & measurable business impact. This guide explains what’s changed, what to expect in interviews, and how to prepare—especially for LLM application, MLOps/platform, data science, AI product & safety roles. Who this is for: AI/ML engineers, LLM engineers, data scientists, MLOps/platform engineers, AI product managers, applied researchers & safety/governance specialists targeting roles in the UK.