Account Executive

Leeds

11 months ago

Applications closed

Related Jobs

View all jobs

Data Analyst - Insurance

Data Engineer

Senior Data Analyst - ( Hybrid) Belfast

Senior Performance & Data Analyst

Head of Data Science and AI

Developer (with Data Engineering focus)

We are excited to be recruiting for a Account Executive to join our West Yorkshire based client, a B2B marketing and campaign management agency specialising in bespoke, tailored customer engagement campaigns on behalf of international clientele. This dynamic role offers the opportunity to manage a range of responsibilities, including overseeing projects and critical paths, building strong client relationships, website management, and data analysis.

Alongside a challenging and dynamic role, you will be rewarded with fantastic benefits and tailored career development. Our client offers a flexible working environment, with hybrid working and flexible hours. Benefits include a generous holiday and pension allowance, private healthcare, a quarterly bonus scheme, as well as commitment to training and a structured path of development with regular salary reviews.

Key Responsibilities of the Account Executive:

Create and manage end-to-end project plans for campaign launches.
Work collaboratively with internal marketing and design teams, as well as external developers, to oversee website builds, branding, and print processes.
Maintaining strong client relationships during and after the launch of the scheme with weekly and monthly campaign review meetings.
Lead client meetings and presentations, providing complex reporting and insights into campaign performance and figures, and make recommendations.
Work with the Data Analyst to provide financials and performance insights.
Regularly monitor sales data, flagging concerns or anomalies.
Oversee financial processes, including invoicing and liaising with suppliers.

Our client is seeking a strong communicator who can effectively engage with both internal teams and external stakeholders. The ideal candidate will possess excellent organisational skills, the ability to collaborate seamlessly across the business, and the eagerness to learn and develop professionally.

Essential Skills and Personal Attributes for the Account Executive:
A can-do, proactive, and driven approach to your work.
Excellent organisational skills, able to follow detailed processes with a focus on accuracy.
A focus on collaboration, a keen team player with motivation and eagerness to learn.
Customer service and confidence in professional communication.
Naturally analytical, able to review data and provide insights.
Analytical mindset with the ability to manage multiple clients.
Proficiency in Microsoft Office (Excel, PowerPoint, Word).

Desirable Experience:
Proficient user of Microsoft Office (good use of Excel is desirable, but not essential).
Any exposure to B2B marketing is useful but not essential. An interest in this is key.
Any experience with B2B client management is useful but not essential.

Due to the number of responses we receive, unfortunately we are unable to give feedback to all individuals. If you have not heard back within 7 days, please assume that you have not been successful for the role you have applied for

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

Industry Insights

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

Feb 3, 2026

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.

Jan 29, 2026

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.

Jan 24, 2026

Education

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.