Research Manager - Quantitative

Aspire
London
1 year ago
Applications closed

Related Jobs

View all jobs

Research Manager / Associate Director (Quantitative)

Research Manager (Quantitative)

Research Manager (Quantitative)

Senior Quantitative Research Manager – Pharma Insights

Quantitative Research Manager - Tech and AI Empowered Research Agency

Senior Quantitative Research Manager - Healthcare Insights

Are you a Research Manager looking to work on end-to-end quantitative projects? Then you could be the perfect fit for this market research company in this flexible Research Manager role!

JOB TITLE: Research Manager
SALARY: Up to £48k
LOCATION: London

A market research agency who focus on delivering more than data for their clients. They are passionately curious experts who not only shape their insights to the markets they are working in, but also to the True Understanding of society and People.

They utilise the best science, technology and know-how and apply this speed, simplicity, security and substance to everything they do. An organisation which has real curiosity and a client first mindset have been driving forward in the industry, collaborating with their clients to make market research the best it possibly can.

They are currently looking to bring on a Research Manager level candidate, who has experience in or is looking to work on end-to-end customer experience studies for a variety of clients.


Key duties

Lead and manage end-to-end quantitative research Take ownership and lead day-to-day client conversations on project and wider account related topics. Effectively manage resources and workloads across the project team, supporting our drive for efficient working and continuous improvement.


Skills & Experience

Proven track record working in an agency or similar environment, with the ability to act as a main client contact Strong experience in quantitative research, alongside team management Ability to build great relationships with clients


Interested in this Research Manager role? Apply now and let's have a chat!

We Are Aspire Ltd are a Disability Confident Commited employer

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 Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Thinking about switching into data science in your 30s, 40s or 50s? You’re far from alone. Across the UK, businesses are investing in data science talent to turn data into insight, support better decisions and unlock competitive advantage. But with all the hype about machine learning, Python, AI and data unicorns, it can be hard to separate real opportunities from noise. This article gives you a practical, UK-focused reality check on data science careers for mid-life career switchers — what roles really exist, what skills employers really hire for, how long retraining typically takes, what UK recruiters actually look for and how to craft a compelling career pivot story. Whether you come from finance, marketing, operations, research, project management or another field entirely, there are meaningful pathways into data science — and age itself is not the barrier many people fear.

How to Write a Data Science Job Ad That Attracts the Right People

Data science plays a critical role in how organisations across the UK make decisions, build products and gain competitive advantage. From forecasting and personalisation to risk modelling and experimentation, data scientists help translate data into insight and action. Yet many employers struggle to attract the right data science candidates. Job adverts often generate high volumes of applications, but few applicants have the mix of analytical skill, business understanding and communication ability the role actually requires. At the same time, experienced data scientists skip over adverts that feel vague, inflated or misaligned with real data science work. In most cases, the issue is not a lack of talent — it is the quality and clarity of the job advert. Data scientists are analytical, sceptical of hype and highly selective. A poorly written job ad signals unclear expectations and immature data practices. A well-written one signals credibility, focus and serious intent. This guide explains how to write a data science job ad that attracts the right people, improves applicant quality and positions your organisation as a strong data employer.

Maths for Data Science Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are applying for data science jobs in the UK, the maths can feel like a moving target. Job descriptions say “strong statistical knowledge” or “solid ML fundamentals” but they rarely tell you which topics you will actually use day to day. Here’s the truth: most UK data science roles do not require advanced pure maths. What they do require is confidence with a tight set of practical topics that come up repeatedly in modelling, experimentation, forecasting, evaluation, stakeholder comms & decision-making. This guide focuses on the only maths most data scientists keep using: Statistics for decision making (confidence intervals, hypothesis tests, power, uncertainty) Probability for real-world data (base rates, noise, sampling, Bayesian intuition) Linear algebra essentials (vectors, matrices, projections, PCA intuition) Calculus & gradients (enough to understand optimisation & backprop) Optimisation & model evaluation (loss functions, cross-validation, metrics, thresholds) You’ll also get a 6-week plan, portfolio projects & a resources section you can follow without getting pulled into unnecessary theory.