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

Apply Now

Systematic Macro Quantitative Researcher

Undisclosed
10 months ago
Applications closed

Related Jobs

View all jobs

Data Scientist (Commodities) | Top Systematic Fund

Machine Learning Platform Engineer - Bonhill Partners

Quantitative Researcher – Machine Learning-Driven Systematic Trading Firm (London)

Machine Learning / Software Engineer - Trading

Research Fellow in Machine Learning for Environmental Modelling

Machine Learning Researcher

Our client, a globally established and highly prestigious multi-platform Hedge Fund, are seeking a Systematic Macro Quant Researcher to join a newly created team within their business. In this dynamic and collaborative role, you will be responsible for developing and implementing cutting-edge quantitative models and strategies across global macro markets and asset classes. You will work closely with world-class researchers, portfolio managers, and technologists to identify and capitalize on inefficiencies in a wide range of asset classes, including equity indexes, fixed income, rates, commodities and FX. You will also help to systematise processes across teams, and build out the systematic infrastructure within the business.Key Responsibilities:Quantitative Research & Strategy Development: Conduct rigorous quantitative research to identify market inefficiencies and develop systematic trading strategies. Utilize statistical, econometric, and machine learning techniques to model macroeconomic relationships and forecast asset prices.Data Analysis & Signal Generation: Analyse large and complex datasets, including macroeconomic indicators, market prices, and alternative data sources, to extract predictive signals. Employ advanced data science methodologies to enhance the robustness and accuracy of models.Model Implementation & Optimization: Collaborate with the technology and trading teams to build and implement quantitative infrastructure, models and strategies in a live trading environment. Continuously optimize and refine models to adapt to changing market conditions.Risk Management: Work closely with risk management teams to assess and manage the risks associated with trading strategies. Develop risk models that account for various market scenarios and stress conditions.Requirements:Strong academic background: Ph.D. or Master's degree in a quantitative discipline such as Economics, Finance, Mathematics, Statistics, Computer Science, or a related field.Strong programming skills in Python, R, or a similar language, and the ability to write clean code.Experience with statistical analysis, econometrics, and machine learning techniques.Proficiency in working with large datasets and data analysis tools.Familiarity with financial markets and economic theory.Proven track record of developing and implementing successful quantitative trading strategies, preferably within a global macro context.3-5 years’ experience in a high-performance trading environment, such as a hedge fund, proprietary trading firm, or investment bank.Due to demand, we are advertising this role anonymously. If you would prefer to speak to someone before submitting a CV, please send a blank application to the role and someone will be in touch to discuss. We can only respond to highly qualified candidates.

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.