Sales Development Representative

This Is Prime
Leeds
1 year ago
Applications closed

Related Jobs

View all jobs

Sales Data Analyst – Finance Sector

Data Analyst – Self-Serve Dashboards & Insights (6-month)

Junior Data Analyst

Data Science Consultant

Data Engineer

Data Science Consultant

Business Development Executive

Location: Leeds City Centre (Hybrid Working)

Salary: £25K - £26K basic, OTE £35-40K

Sector: Marketing/Events/Tech/Software


The Company:

Our client are an outsourced business development and marketing department that help b2b companies across the globe focusing in on the UK, US, Europe, China and APAC to win new clients and grow their business. Their clients range from tech giants and disruptors including household names like Google, Adobe, Verizon, and Steven Bartlett's company Social Chain!

Founded in 2012, the company has gone from strength to strength and now with a team of over 55 people based out of their London HQ, they boast an impressive client portfolio, a vibrant city office location, and a truly collaborative and social environment. They're now looking to expand across the Globe but beginning with Manchester and Leeds.

You’ll research then build a list of prospects that hit the client ICP brief, invite them along to events where they can hear from expert speakers typically on a challenge they might be facing, and you'll then look to generate sales meetings post- event. You’ll also get to attend these events which are hosted at cool venues such as Soho House, The Shard and The Gerkin.


The Benefits:

  • Competitive salary and uncapped commission
  • Clear and structured progression path – 1st promotion within your first year
  • Opportunity to work with some of the biggest tech companies worldwide
  • Monthly team socials paid by the company
  • Hybrid working
  • Dedicated Line manager who will help plan your working week and drive your personal development.
  • Lots of clubs and activities – i.e., book club / yoga / 5 a side football / regular social events


The Role:

  • Generate attendees to client webinars & events. You’ll reach out to prospects via LinkedIn, the phone and email.
  • Support the wider Business Development team on various client accounts – helping to build and nurture new business leads and relationships.
  • Generate new leads from cold by leveraging insight, content, events and trends to spark the conversation.
  • Schedule meetings and demos for your clients with prospects who would be interested in the clients’ products.
  • Communicate with clients and undertake general account management responsibilities such as compiling reporting documents and ensuring your client has all the information about the leads you generate.
  • Work towards monthly targets focused on a set amount of meetings booked and attended and/or event registration sign ups comprising of digital and in-real-life events.


You Should Apply If:

  • Have any kind of office working experience
  • Have fantastic communication skills both verbal and written
  • If you’re a team player whilst maintaining an ambitious and competitive mindset
  • Have the ability to grasp new topics and acquire new skills quickly
  • Be curious and have a solution focused mindset, always finding a way to overcome challenges and deliver results
  • Be incredibly coachable and willing to learn
  • Possess excellent organisational skills

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.

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.

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.

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.

🍪 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.