Digital Marketing Manager

London
1 month ago
Applications closed

Related Jobs

View all jobs

PPC Account Manager

Senior Product Manager - AI, ML & Data Science

Product Director - Digital Health

Digital Marketing Executive (CRO)

Paid Search Lead

Principal Data Science Consultant with Marketing Expertise

Digital Marketing Lead
£70,000 - £90,000
London - 3 days per week

My client is a well-established financial software platform – providing access to the world’s major commodity markets and facilitating over 50million trades around the globe.
Established in 2005, with over 1800 employees around the world – they are embarking on ambitious growth plans and seeking to hire their 1st dedicated Digital Marketing Lead to oversee and optimise their digital touch points, improve business intelligence and overhaul the marketing offering.  
Apply Now – if you would like to join an ambitious financial software platform and play a key role in their Digital Marketing offering and ongoing success.
 
The Role

Develop and execute digital marketing strategies to enhance brand visibility and customer engagement.
Drive traffic to digital platforms through SEO, PPC, social media, email marketing, and content strategies.
Work closely with data analysts and UX designers to refine marketing strategies and improve user experience.
Utilise analytics to measure performance, generate insights, and refine marketing activities.
Oversee the development of digital campaigns, ensuring alignment with business objectives.
Manage and collaborate with internal teams and external partners to deliver impactful marketing initiatives.
Implement and manage marketing tools such as HubSpot, Salesforce, and other automation platforms.
Develop dashboards to track key marketing performance metrics, including website and LinkedIn analytics. 
Skills and Experience:

Proven experience in digital marketing, with a track record of driving audience growth and engagement across different channels including SEO, PPC, social media, email marketing, and content marketing.
Experience in using analytics tools (e.g. Google Analytics, SEMrush, Adobe Analytics) to inform decision-making.
Familiarity with marketing tools such as HubSpot and Salesforce.
Experience in dashboard creation to monitor digital marketing performance.
Knowledge of CRM, marketing automation, and customer segmentation strategies.Strong entrepreneurial spirit with the ability to lead initiatives and drive digital marketing transformation within the organisation.Excellent communication and stakeholder management skills.

Digital Marketing Lead
£70,000 - £90,000
London - 3 days per week

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Jobs

Portfolio Projects That Get You Hired for Machine Learning Jobs (With Real GitHub Examples)

In today’s data-driven landscape, the field of machine learning (ML) is one of the most sought-after career paths. From startups to multinational enterprises, organisations are on the lookout for professionals who can develop and deploy ML models that drive impactful decisions. Whether you’re an aspiring data scientist, a seasoned researcher, or a machine learning engineer, one element can truly make your CV shine: a compelling portfolio. While your CV and cover letter detail your educational background and professional experiences, a portfolio reveals your practical know-how. The code you share, the projects you build, and your problem-solving process all help prospective employers ascertain if you’re the right fit for their team. But what kinds of portfolio projects stand out, and how can you showcase them effectively? This article provides the answers. We’ll look at: Why a machine learning portfolio is critical for impressing recruiters. How to select appropriate ML projects for your target roles. Inspirational GitHub examples that exemplify strong project structure and presentation. Tangible project ideas you can start immediately, from predictive modelling to computer vision. Best practices for showcasing your work on GitHub, personal websites, and beyond. Finally, we’ll share how you can leverage these projects to unlock opportunities—plus a handy link to upload your CV on Machine Learning Jobs when you’re ready to apply. Get ready to build a portfolio that underscores your skill set and positions you for the ML role you’ve been dreaming of!

Jobs Careers

Machine Learning Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Machine learning is fuelling innovation across every industry, from healthcare to retail to financial services. As organisations look to harness large datasets and predictive algorithms to gain competitive advantages, the demand for skilled ML professionals continues to soar. Whether you’re aiming for a machine learning engineer role or a research scientist position, strong interview performance can open doors to dynamic projects and fulfilling careers. However, machine learning interviews differ from standard software engineering ones. Beyond coding proficiency, you’ll be tested on algorithms, mathematics, data manipulation, and applied problem-solving skills. Employers also expect you to discuss how to deploy models in production and maintain them effectively—touching on MLOps or advanced system design for scaling model inferences. In this guide, we’ve compiled 30 real coding & system‑design questions you might face in a machine learning job interview. From linear regression to distributed training strategies, these questions aim to test your depth of knowledge and practical know‑how. And if you’re ready to find your next ML opportunity in the UK, head to www.machinelearningjobs.co.uk—a prime location for the latest machine learning vacancies. Let’s dive in and gear up for success in your forthcoming interviews.

Jobs

Negotiating Your Machine Learning Job Offer: Equity, Bonuses & Perks Explained

How to Secure a Compensation Package That Matches Your Technical Mastery and Strategic Influence in the UK’s ML Landscape Machine learning (ML) has rapidly shifted from an emerging discipline to a mission-critical function in modern enterprises. From optimising e-commerce recommendations to powering autonomous vehicles and driving innovation in healthcare, ML experts hold the keys to transformative outcomes. As a mid‑senior professional in this field, you’re not only crafting sophisticated algorithms; you’re often guiding strategic decisions about data pipelines, model deployment, and product direction. With such a powerful impact on business results, companies across the UK are going beyond standard salary structures to attract top ML talent. Negotiating a compensation package that truly reflects your value means looking beyond the numbers on your monthly payslip. In addition to a competitive base salary, you could be securing equity, performance-based bonuses, and perks that support your ongoing research, development, and growth. However, many mid‑senior ML professionals leave these additional benefits on the table—either because they’re unsure how to negotiate them or they simply underestimate their long-term worth. This guide explores every critical aspect of negotiating a machine learning job offer. Whether you’re joining an AI-focused start-up or a major tech player expanding its ML capabilities, understanding equity structures, bonus schemes, and strategic perks will help you lock in a package that matches your technical expertise and strategic influence. Let’s dive in.

🍪 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.