Paid Search Lead

London
9 months ago
Applications closed

Related Jobs

View all jobs

Data Engineer: Build Scalable Pipelines & AI Dashboards

Recruitment Consultant - Pharmaceutical/Biotech Data Science

Junior Data Analyst

Data Engineer

Machine Learning Scientist I - Performance Marketing

Data Engineer - AI Practice Team

Job Title: Digital Marketing Lead - Paid Search

Location: London HQ (hybrid)

About the Role

We are looking for a dynamic and results-driven Paid Search Lead to drive the growth of our Paid Search program globally. The role is pivotal in meeting our revenue and efficiency targets, with accountability for performance against Paid Search targets globally.

What You'll Be Doing

  • Strategy: Working with the Head of Performance Marketing and team of channel specialists to develop and execute a comprehensive global Paid Search strategy to drive growth and achieve ambitious revenue and efficiency targets.

  • Performance management: Be hands on in our accounts, optimising a complex, high-spending global Paid Search program across all major search engines.

  • Industry trends: Stay up to date with the latest trends and innovations in Paid Search and digital marketing, including AI-driven advertising and automation, to ensure our strategies remain cutting-edge. Work closely with platform partners to stay on top of emerging products and ensure we have a plan to test them at pace.

  • Testing and optimisation: Implement A/B testing and continuous optimisation of campaigns to enhance performance and drive growth.

  • Data analysis: Utilise enterprise analytics tools such as Looker to analyse campaign performance.

  • Reporting and insights: Generate detailed reports, dashboards and actionable insights for the team and for our stakeholders, demonstrating the impact of paid search on overall business objectives. Conduct analysis on competitor activity and make clear recommendations to improve our position in the market.

  • Collaboration: Work closely with Product, Data Science, and Engineering teams to develop technical solutions and enhance campaign performance.

  • Budget setting: Assist in setting and managing a large annual budget that covers all our global markets.

  • Stakeholder management: Communicate effectively with stakeholders, demonstrating a strong bias for action and ability to simplify complexity to get buy-in for our projects.

    What We’re Looking For

  • Technical expertise: 5+ years hands-on and deep experience with Google Ads and Microsoft Ads. Experience working with ad platform APIs and scripts to drive automation.

  • Analytical skills: Highly analytical and data-driven, comfortable working independently with data. Experience with SQL is a bonus.

  • Experience: Proven track record in managing complex and high-spending global accounts, ideally within e-commerce or marketplace businesses.

  • Cultural fit: Strong communicator with a growth mindset, passionate about Deliveroo's mission and growth ambitions. Ability to rally a team around a goal and pivot quickly when presented with new information.

    • Bias for action: Demonstrates a proactive approach to driving results and solving problems.

    • Test and learn mindset: Embraces experimentation and iterative improvement.

    • Growth mindset: Continuously seeks opportunities for learning and development.

      Why Deliveroo

      Our mission is to be the definitive food company. We are transforming the way the world eats by making food more convenient and accessible. We give people the opportunity to eat what they want, as they want it, when and where they want it.

      We are a technology-driven company at the forefront of the most rapidly expanding industry in the world. We are still a small team, making a very large impact, looking to answer some of the most interesting questions out there. We move fast, value autonomy and ownership, and we are always looking for new ideas.

      Workplace & Benefits

      At Deliveroo we know that people are the heart of the business and we prioritise their welfare. Benefits differ by country, but we offer many benefits in areas including healthcare, well-being, parental leave, pensions, and generous annual leave allowances, including time off to support a charitable cause of your choice. Benefits are country-specific, please ask your recruiter for more information.

      Diversity

      At Deliveroo, we believe a great workplace is one that represents the world we live in and how beautifully diverse it can be. That means we have no judgement when it comes to any one of the things that make you who you are - your gender, race, sexuality, religion or a secret aversion to coriander. All you need is a passion for (most) food and a desire to be part of one of the fastest-growing businesses in a rapidly growing industry.

      We are committed to diversity, equity and inclusion in all aspects of our hiring process. We recognise that some candidates may require adjustments to apply for a position or fairly participate in the interview process. If you require any adjustments, please don't hesitate to let us know. We will make every effort to provide the necessary adjustments to ensure you have an equitable opportunity to succeed

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.