Commercial Data Analyst

Harnham
Merton
8 months ago
Applications closed

Related Jobs

View all jobs

Audience & Campaign Data Analyst — 1st-Party Data & BI

Senior Data Analyst

Senior Data Analyst

Senior Data Analyst

Data Analyst

Marketing Data Analyst – Drive Growth & Insights

📊 Commercial Data Analyst
💰 Up to £80,000
📍 Hybrid - 4 days/week in South West London (5 days during first 3 months)

A digitally-led retail brand within a well-established retail group is hiring aCommercial Data Analystto help drive smarter, faster decisions across the business. With a balanced mix of e-commerce and brick-and-mortar, the business is profitable and growing-with ambitious digital growth targets for the year ahead.

As thesole embedded data expertin the brand team, you'll work across Digital, Marketing, Buying, Finance, and Exec stakeholders-responding to ad hoc requests, delivering insightful reporting, and most importantly, using data toproactively influence strategy.

Example projects:

  • Spot sales trends (e.g. weather-driven demand spikes) and recommend agile trading or campaign decisions

  • Support new store expansion strategy by analysing customer location, order frequency, and market viability

  • Evaluate marketing ROI using tools like Fospha and GA; lead incrementality testing across paid channels

  • Integrate new data sources (e.g. research, attribution, or behavioural data) to enrich customer understanding

🔍 About you:

  • 3+ years in a data analytics or insight role

  • Strong SQL, experience with BigQuery preferred

  • Exposure to Python for analysis/modelling

  • Skilled in data visualisation (Looker, Tableau, Power BI, etc.)

  • Experience in digital, marketing or customer analytics

  • E-commerce or retail background a plus

  • Naturally curious and proactive-you spot trends and ask questions before others do

Tech Stack:BigQuery (SQL), Python, Looker, Fospha, GA, ContentSquare

Interview Process:

  • Intro chat with Chief Digital Officer

  • In-person data task with senior stakeholders

  • Optional meeting with other senior leaders (Marketing, Finance, COO)

This is a fantastic opportunity for a commercially-minded analyst to step into a role where your insights will directly shape digital growth and brand strategy.

Interested or know someone perfect? Apply now or DM for more details.

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.

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

Are you considering a career change into machine learning in your 30s, 40s or 50s? You’re not alone. In the UK, organisations across industries such as finance, healthcare, retail, government & technology are investing in machine learning to improve decisions, automate processes & unlock new insights. But with all the hype, it can be hard to tell which roles are real job opportunities and which are just buzzwords. This article gives you a practical, UK-focused reality check: which machine learning roles truly exist, what skills employers really hire for, how long retraining realistically takes, how to position your experience and whether age matters in your favour or not. Whether you come from analytics, engineering, operations, research, compliance or business strategy, there is a credible route into machine learning if you approach it strategically.

How to Write a Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market — it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.

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

Machine learning job adverts in the UK love vague phrases like “strong maths” or “solid fundamentals”. That can make the whole field feel gatekept especially if you are a career changer or a student who has not touched maths since A level. Here is the practical truth. For most roles on MachineLearningJobs.co.uk such as Machine Learning Engineer, Applied Scientist, Data Scientist, NLP Engineer, Computer Vision Engineer or MLOps Engineer with modelling responsibilities the maths you actually use is concentrated in four areas: Linear algebra essentials (vectors, matrices, projections, PCA intuition) Probability & statistics (uncertainty, metrics, sampling, base rates) Calculus essentials (derivatives, chain rule, gradients, backprop intuition) Basic optimisation (loss functions, gradient descent, regularisation, tuning) If you can do those four things well you can build models, debug training, evaluate properly, explain trade-offs & sound credible in interviews. This guide gives you a clear scope plus a six-week learning plan, portfolio projects & resources so you can learn with momentum rather than drowning in theory.