Digital Marketing Manager

STOPGAP-1
Greater London
1 year ago
Applications closed

Related Jobs

View all jobs

Junior Data Analyst

CDI - Data Engineer (Data Science)

Data Engineer (Data Science)

Junior Data Analyst Norwich

Data Analyst, Marketing Insights — Remote/Part-Time

Data Engineering Manager


We are looking for an experienced Digital Marketing Manager to manage and optimise the performance of a digital marketing agency.

THE COMPANY
A well established insurance company, based in London.

THE ROLE
As Digital Marketing Manager you will be responsible for ensuring the agency delivers across paid search, paid social, SEO and CRO campaigns. Your role will include:
- briefing the agency, setting clear objectives
- managing marketing budgets
- campaign analysis
- campaign optimisation

YOU
To be successful in this Digital Marketing Manager role you MUST have:
- strong understanding of digital marketing campaigns
- proved experience of digital marketing agency management
- PPC, paid social and SEO campaigns
- excellent data analysis, reporting and performance optimisation
- ability to work in central London on a regular basis

You must be fluent in English and have the right to work in the UK.

If you can tick ALL the boxes, then please apply online NOW!

NB: You must be eligible to work in the UK

If this role isn't what you are looking for, don't worry. At Stopgap we cover a wider range of freelance and permanent positions with dedicated sector specialists. It is worth checking our website for all our latest jobs and registering to receive job alerts so you are the first to know about a new opportunity.

Marketing, Digital and Creative Recruitment
Stopgap - Talent With A Spark

a2F0ZS5jcnVtcHRvbi4wNTkwOS40MzlAc2dncm91cG5ldy5hcGxpdHJhay5jb20.gif

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.

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.

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.

The Skills Gap in Machine Learning Jobs: What Universities Aren’t Teaching

Machine learning has moved from academic research into the core of modern business. From recommendation engines and fraud detection to medical imaging, autonomous systems and language models, machine learning now underpins many of the UK’s most critical technologies. Universities have responded quickly. Machine learning modules are now standard in computer science degrees, specialist MSc programmes have proliferated, and online courses promise to fast-track careers in the field. And yet, despite this growth in education, UK employers consistently report the same problem: Many candidates with machine learning qualifications are not job-ready. Roles remain open for months. Interview processes filter out large numbers of applicants. Graduates with strong theoretical knowledge struggle when faced with practical tasks. The issue is not intelligence or effort. It is a persistent skills gap between university-level machine learning education and real-world machine learning jobs. This article explores that gap in depth: what universities teach well, what they routinely miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in machine learning.