National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Market Insight Analyst

ENI – Elizabeth Norman International
Woking
8 months ago
Applications closed

Related Jobs

View all jobs

Data Analyst

Data Analyst

Data Analyst

Senior Pricing Analyst

Data Analyst

Legal Data Analyst & Researcher

Market Insight Analyst

TV & Audio business

Exceptional salary and benefits

Surrey/hybrid - 3x a week in the office


As the Insight Analyst you will be part of the business operations team, owning data sources, data intelligence and providing meaningful insights to support both sales and strategic product decisions.


We are looking for a analyst who is passionate about digging deeper and explaining the "why" and how changes within the data came to be, surface level will not be enough.


There will be reporting responsibilities (using Powerpoint or Excel) on market trends, market share, and market sizing - having a market intelligence background is quite good for this role!


You'll be working closely with various senior stakeholders from the sales, product and project teams to contribute to strategic analysis and provide competitor insights too.



THE CLIENT:

  • They’re a top 10 global brand and one of the world’s favourite technology brands.
  • They have an extensive and award-winning product range spanning Mobile Phones, TV, Computers and White goods and Smart Home products.
  • They are built on an entrepreneurial culture, a spirit of innovation with ambitious business goals.
  • They also have an excellent culture centered around diversity, inclusion and creativity.



Skills Required

  • Minimum 2 years experience working in an insights/analytics focused role

• Strong Excel skills i.e. (Macro and power query – good to have, pivot tables, advanced formulas – is a must)

• Strong analytical skills with the ability to translate data into actionable insights

• Experience providing deeper level of analysis when reporting, not just surface level

• Analytical mindset and proactive at spotting changes in the data and finding methods to fix or explain the change.

• Experience working with market data

• Excellent communication skills, both written and verbal

• Comfortable with big data

•Articulate complex analysis to management and senior staff


Benefits:


  • Hybrid working model: 3 days in the office, 2 days at home per week.
  • Bonus scheme.
  • Pension contribution.
  • 3 volunteering days per year.
  • 25 days of annual leave plus bank holidays and an additional day off for your birthday.
  • Staff sales discounts on a wide range of products.
  • Access to a discount shopping portal.
  • Equal opportunity employer promoting diversity and inclusion.
  • Reasonable accommodations provided for individuals with disabilities.


Even if you feel you don’t hit all of the requirements we’d still encourage you to send in an application.

National AI Awards 2025

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.

Return-to-Work Pathways: Relaunch Your Machine Learning Career with Returnships, Flexible & Hybrid Roles

Returning to work after an extended break can feel like starting from scratch—especially in a specialist field like machine learning. Whether you paused your career for parenting, caring responsibilities or another life chapter, the UK’s machine learning sector now offers a variety of return-to-work pathways. From structured returnships to flexible and hybrid roles, these programmes recognise the transferable skills and resilience you’ve developed, pairing you with mentorship, upskilling and supportive networks to ease your transition back. In this guide, you’ll discover how to: Understand the current demand for machine learning talent in the UK Leverage your organisational, communication and analytical skills in ML contexts Overcome common re-entry challenges with practical solutions Refresh your technical knowledge through targeted learning Access returnship and re-entry programmes tailored to machine learning Find roles that fit around family commitments—whether flexible, hybrid or full-time Balance your career relaunch with caring responsibilities Master applications, interviews and networking specific to ML Learn from inspiring returner success stories Get answers to common questions in our FAQ section Whether you aim to return as an ML engineer, research scientist, MLOps specialist or data scientist with an ML focus, this article will map out the steps and resources you need to reignite your machine learning career.

LinkedIn Profile Checklist for Machine Learning Jobs: 10 Tweaks to Drive Recruiter Interest

The machine learning landscape is rapidly evolving, with demand soaring for experts in modelling, algorithm tuning and data-driven insights. Recruiters hunt for candidates proficient in Python, TensorFlow, PyTorch and MLOps processes. A generic profile simply won’t cut it. Our step-by-step LinkedIn for machine learning jobs checklist covers 10 targeted tweaks to ensure your profile ranks in searches and communicates your technical impact. Whether launching your ML career or seeking leadership roles, these optimisations will sharpen your professional narrative and boost recruiter engagement.

Part-Time Study Routes That Lead to Machine Learning Jobs: Evening Courses, Bootcamps & Online Masters

Machine learning—a subset of artificial intelligence—enables computers to learn from data and improve over time without explicit programming. From predictive maintenance in manufacturing to recommendation engines in e-commerce and diagnostic tools in healthcare, machine learning (ML) underpins many of today’s most innovative applications. In the UK, demand for ML professionals—engineers, data scientists, research scientists and ML operations specialists—is growing rapidly, with roles projected to increase by over 50% in the next five years. However, many aspiring ML practitioners cannot step away from work or personal commitments for full-time study. Thankfully, a rich ecosystem of part-time learning pathways—Evening Courses, Intensive Bootcamps and Flexible Online Master’s Programmes—empowers you to learn machine learning while working. This comprehensive guide examines each route: foundational CPD units, immersive bootcamps, accredited online MSc programmes, funding options, planning strategies and a real-world case study. Whether you’re a software developer branching into ML, a statistician aiming to upskill, or a professional exploring AI-driven innovation, you’ll discover how to build in-demand ML expertise on your own schedule.