Insight Manager

Old Bailey
1 year ago
Applications closed

Related Jobs

View all jobs

16. 12 Quantitative Insight Manager Filter-MARKET RESEARCH

Data Analyst, Experience Insights

Business Intelligence Manager

Business Intelligence Manager

Consultant - Manager, Data Science and Machine Learning, AI & Data, Defence & Security

Consultant - Manager, Data Science and Machine Learning, AI & Data, Defence & Security

Globally developing Market Research Company seeks for an Insight Manager
【Title】
Insight Manager
【Location】
London
【Salary】
£- 45,000
The Insight Manager plays an integral role in achieving successful project outcomes for clients. They work closely with Project Directors while managing Insight Executives to ensure projects run timely and smoothly with accurate, insightful project outcomes that meet our client’s needs. They are generally the key client contact and are expected to take a key role in analysis and reporting so an ability to think strategically is important.
【Key Tasks/ Responsibilities】

  • Play a key role in project brainstorms and contribute to the development and amendment of research materials, working with the Project Director and clients to achieve optimal outcomes.
  • Attend and occasionally run immersion sessions to understand strategic issues and research objectives
  • Attend and contribute to project/client pitches and credentials presentations
  • Oversee all stages of projects, ensuring that ISO standards are met, ensuring fieldwork runs smoothly and project timings are followed closely
  • When project issues/challenges arise, suggest solutions and collaborate towards a positive outcome
  • Ensure that Insight Executives and data analysts produce data that is clean and correctly coded before analysis or client delivery
  • Work on PowerPoint report development, and work with design team for additional report outputs
  • Attend and contribute to client presentations, build and maintain proactive relationships with clients, providing regular updates
  • Work with the Project Director to develop recommendations and implications for future client strategy, identifying opportunities for account expansion
  • Mentor, supervise, contribute to training, and participate in learning and development activities of Executives and Graduates
  • Line management and conducting formal appraisals of Executives
  • Support senior team members to design optimal research, developing proposals based on client briefs, sourcing costs from external suppliers – understand and manage project pricing, costing and budget
  • Contribute to marketing initiatives and proprietary research, demonstrate clear understanding of company targets and how each role contributes to achievement of these

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.

Education Jobs

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.

Jobs

Neurodiversity in Data Science Careers: Turning Different Thinking into a Superpower

Data science is all about turning messy, real-world information into decisions, products & insights. It sits at the crossroads of maths, coding, business & communication – which means it needs people who see patterns, ask unusual questions & challenge assumptions. That makes data science a natural fit for many neurodivergent people, including those with ADHD, autism & dyslexia. If you’re neurodivergent & thinking about a data science career, you might have heard comments like “you’re too distracted for complex analysis”, “too literal for stakeholder work” or “too disorganised for large projects”. In reality, the same traits that can make traditional environments difficult often line up beautifully with data science work. This guide is written for data science job seekers in the UK. We’ll explore: What neurodiversity means in a data science context How ADHD, autism & dyslexia strengths map to common data science roles Practical workplace adjustments you can request under UK law How to talk about your neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in data science – & how to turn “different thinking” into a real career advantage.

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.

🍪 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.