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

Apply Now

Quantitative Research Lead

Selby Jennings
1 year ago
Applications closed

Related Jobs

View all jobs

Senior Manager of Quantitative Research Location: London

Senior User Researcher - Agentic AI / Quantitative Research - Outside IR35

Senior User Researcher - Agentic AI / Quantitative Research - Outside IR35

Senior User Researcher - Agentic AI / Quantitative Research - Outside IR35

Quantitative Researcher - Experienced

Quantitative Research Director (Tracking focus)

I am working with a pod at a tier-1 multi-manager who are looking for a quantitative research lead to be based in London.

Key Responsibilities:

Lead and manage a team of quantitative researchers and analysts. Develop, backtest, and implement systematic trading strategies across various asset classes. Conduct in-depth research to identify new investment opportunities and enhance existing strategies. Utilise advanced statistical and machine learning techniques to analyse large datasets and uncover market inefficiencies. Collaborate with portfolio managers and other teams to integrate research findings into the investment process. Stay abreast of the latest developments in quantitative finance, data science, and financial markets. Present research findings and strategy performance to senior management and stakeholders.

Qualifications:

Ph.D. is preferred 5 - 10 years of experience in quantitative research and strategy development within a hedge fund. Strong programming skills in languages such as Python, R, or C++. Proficiency in data analysis, statistical modelling, and machine learning techniques. Excellent problem-solving skills and attention to detail. Strong communication and leadership skills with the ability to work effectively in a team-oriented environment. Proven ability to manage multiple projects and meet tight deadlines.

Benefits:

Competitive salary and performance-based bonuses. Generous paid time off and flexible working hours. Professional development opportunities and continuous learning initiatives. Collaborative and inclusive company culture.

If interested, please let me know by applying directly or emailing me: harry.moore(at)selbyjennings.com

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.

Jobs

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Jobs

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

Jobs

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.