Sales Manager – Exhibitions

Marylebone High Street
11 months ago
Applications closed

Related Jobs

View all jobs

Sales Data Analyst

Data Analytics Manager - Heartwood Collection

Data Analyst

Data Analyst - Farming Operations

Data Analyst Placement Programme

Data Analyst

Sales Manager – Hospitality Exhibitions

£45,000 - £53,000 + Commission + Excellent Benefits

Hybrid

Leading media events business seeks a highly talented senior Exhibition Sales Manager to join their sales team both selling across an industry leading hospitality expo as well as managing a junior sales exec. This role will focus on developing a tech focused area of an industry leading show.

This position involves a large mix of key accounts and new business with regular face to face meetings at industry events and international travel 5-6 times a year.

You will lead and support part of the sales team, providing guidance, training, and development to enhance team members’ performance and professional growth.

This role has fast-track progression, within 12 months the plan is for this role to move into leadership with strategic and organisational responsibilities. We are looking for a highly drive, ambitious sales person who is results focused and has a strong interest in tech/events.

Candidate Profile:

  • Minimum of 3 years of exhibition sales experience and a proven track record of driving sales results.

  • Demonstrated success in achieving results within exhibitions and sponsorship sales, consistently meeting and exceeding targets.

  • Highly organised, with the ability to effectively prioritise and manage time to maximize productivity and achieve goals.

  • High emotional intelligence, skilled in building and sustaining strong relationships with both internal and external stakeholders.

  • Personable and enthusiastic, with a proactive, solutions-oriented approach—a true team player committed to collective success.

  • Lipton Media is a specialist media recruitment agency based in London. We specialise in all forms of b2b media sales including conferences, exhibitions, awards, summits, publishing, digital, outdoor, TV, radio and business intelligence.

    Our clients range from small start-up companies to FTSE 100 and 250 businesses.

    We work with people at every stage of their career from undergraduates looking for their first entry point into sales to senior managers and directors looking for their next challenge

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.

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.

The Skills Gap in Data Science Jobs: What Universities Aren’t Teaching

Data science has become one of the most visible and sought-after careers in the UK technology market. From financial services and retail to healthcare, media, government and sport, organisations increasingly rely on data scientists to extract insight, guide decisions and build predictive models. Universities have responded quickly. Degrees in data science, analytics and artificial intelligence have expanded rapidly, and many computer science courses now include data-focused pathways. And yet, despite the volume of graduates entering the market, employers across the UK consistently report the same problem: Many data science candidates are not job-ready. Vacancies remain open. Hiring processes drag on. Candidates with impressive academic backgrounds fail interviews or struggle once hired. The issue is not intelligence or effort. It is a persistent skills gap between university education and real-world data science roles. This article explores that gap in depth: what universities teach well, what they often miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data science.