Lead Data Analyst

Love2shop
Liverpool
1 year ago
Applications closed

Related Jobs

View all jobs

Lead Data Analyst

Lead Data Analyst

Lead Data Analyst

Lead Data Analyst

Lead Data Analyst: Experimentation & Personalisation (Hybrid)

Lead Data Analyst and Insights

About the Job

Role: Lead Data Analyst

Hybrid Role: 2/3 days in office/WFH

Office location: Liverpool city centre (L3)


Who We Are❤️

Welcome to Love2shop! We’re a vibrant company that helps people celebrate life’s special moments—at home, work, play, and anywhere else. How do we do it? By offering a fantastic range of gift cards and vouchers that open the door to hundreds of top high street brands and retailers.



We’re big in both consumer and business markets, with over 60% of the UK recognizing our brand. That’s a lot of people loving what we do!


With 55+ years under our belt, we know our stuff. But we’re not just about the past—we’re forward-thinking and progressive. We recently joined the PayPoint family, and we’ve got some exciting developments on the horizon.


As a disability-confident committed company, we’re all about championing equality. We welcome everyone—regardless of disability, age, race, religion, gender identity, or sexual orientation. Everyone gets a shot at success here at Love2shop.❤️


Join Us! ❤️


We’re on the lookout for aLead Data Analystto join us at Love2shop. This role is the perfect fit for someone who likes managing/developing a team but likes to stay 'hands on' by delivering actionable insight for multiple Love2shop B2C and B2B brands.


This is a crucial role for the business, you will lead the build of a fully automated suite of reports to bring insights to the business and support decision making, identify improvement opportunities with existing processes to get them fully automated and system-driven.


Not only that work closely with the business and BI teams to gather requirements for data improvements, and deliver self-serve reporting to reduce manual inputs and errors, and drive greater visibility of the data and trends.




Main Responsibilities ❤️


  • Set customer segmentation, analyse and report on customer behaviours and provide an understanding of customer acquisition, retention and lifetime value to help form strategic sales, marketing, channel and product plans
  • Build reporting and set relevant KPI’s to the appropriate business areas for Commercial Finance
  • Work closely with Marketing and Digital Marketing to produce reporting to give visibility of customer trends across their lifecycle and across all customer touchpoints, to show positive and negative trends of acquisition and retention of customers, and to analyse marketing effectiveness
  • Own the customer, using insights to form customer profiles to aid internal departments plan their strategy and activity
  • Gather retailer and customer insights to inform marketing promotional and strategic opportunities with retailers
  • Proactively have frequent contact with stakeholders to provide actionable insight around marketing channels, customer and business performance and market trends along with response to ad hoc requests
  • Oversee and deliver end-to-end machine learning models to give greater insights and better data, with actionable reporting
  • Track the impact of marketing campaigns, policy changes, and other customer actions to allow for better future decision making


Essentials skills required ❤️



  • Ability to investigate, interpret and translate data into actionable insight
  • Understanding of customer segmentation techniques, customer acquisition and lifetime values, predictive analytics and forecasting
  • Expert of data manipulation and programming in SQL
  • Expert of Data Visualisation tools such as Power BI, Tableau, etc.
  • Experience in marketing campaign analysis
  • Can demonstrate commercial awareness with an understanding of the retail environment
  • Team player with proven leadership skills
  • Excellent presentation skills


Desirable but not essential ❤️



  • Understanding of ETL processes
  • Ability to understand, create and use efficient data models
  • Knowledge of best practices within SQL, to create efficient code, stored procedures and views
  • Good knowledge of python, and the ability to implement Machine Learning and data science techniques
  • Experience with Microsoft Fabric


Benefits if you decide to join us ❤️



  • 25 days’ holiday + bank holidays ️
  • Company pension scheme
  • UK health care cover
  • Discounts with multiple UK retailers ️
  • Fabulous kitchen space with free tea, coffee and snacks ☕
  • Family-friendly leave
  • Community volunteering policy
  • Regular company-wide social events ✨




Ready to join the fun? If you're interested in apermanent role & hybrid working, apply now and join a talented group of people who love what they do.❤️

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.

Careers

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

Jobs

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

Careers Jobs

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.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.