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

Apply Now

Quantitative Research Manager

London
11 months ago
Applications closed

Related Jobs

View all jobs

Quantitative or Integrated Research Manager

Senior Research Executive (Quantitative)

Senior Research Executive (Quantitative)

Quantitative Equity Research Analyst/Portfolio Manager

Quantitative Equity Research Analyst/Portfolio Manager

Quantitative Insights Manager

Quantitative Research Manager Hybrid (London), £35-45,000 

If you love a role working with a variety of client within many sectors including Consumer, FMCG, Media, Tech and Utilities then this is the role for you!  

The role will be 2-3 days a week in their London office.

The person our client is looking for is:

Well versed in and willing to take an active role in leading the entire insight project lifecycle, from brief through to delivery (awareness of both qualitative and quantitative project lifecycles is a bonus)

Strong analytical skills including conjoint, MaxDiff and Segmentation

Interested in how technology can help them improve and enhance the insight generation process

A self-starter, and confident enough to be autonomous, and take on a variety of projects and responsibilities with minimal supervision

Keen to be involved in thinking beyond a project-by-project basis, leading or co-leading client liaison and taking an active role in your own career development

You will have:

At least three years background within an insight agency

Diversity in project experience, covering both quantitative tracking and ad hoc projects (qualitative experience would be a bonus)

Experience in managing supplier and/or client relationships

Technical (hands on) experience in data-processing ideally using Q, but could be using other programmes like SPSS or R

Creative flair, with an interest in making insight beautiful

Accuracy and attention to detail in all elements of their work, both written and verbal

Bravery in producing strong work for clients, and sharing your views both internally and externally

A desire to learn and grow, and be part of a team that is going places

You will need the Right to Work in the UK and be able to attend the London office 2-3 times per week.

Please get in touch for more info

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.

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.

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.

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.