Data Sales Manager

Shaw Daniels Solutions
London
1 month ago
Applications closed

Related Jobs

View all jobs

Business Development Manager (Staffing Solutions)

Business Development Manager (Staffing Solutions)

Clinical Data Scientist

Data Engineering Manager

Senior Product Manager - AI, ML & Data Science

Procurement Analyst Manager

Data Sales Leader

Location: London

Job Summary

Our clients are seeking a dynamic, results-oriented Data Sales Leader to drive their go-to-market strategy for data solutions. This individual will be instrumental in leading sales initiatives, growing revenue, and expanding their enterprise customer base. The ideal candidate brings deep expertise in selling data products, analytics platforms, or data-driven services, and can effectively translate data capabilities into real business value. Collaboration across cross-functional teams will be key to delivering impactful, tailored solutions.

Key Responsibilities

  • Own and lead the full sales cycle for data and analytics offerings.
  • Design and execute strategic sales plans to achieve and surpass revenue targets.
  • Identify new enterprise opportunities and expand into emerging verticals.
  • Cultivate and manage long-term relationships with key clients and decision-makers.
  • Partner with product, marketing, and customer success teams to align solutions with client needs.
  • Translate business challenges into data-driven solutions that resonate with enterprise clients.
  • Provide accurate sales forecasting and report on key performance indicators (pipeline, revenue, conversion rates).
  • If applicable, recruit, mentor, and manage a high-performing sales team.
  • Stay informed on industry trends, emerging data technologies, and the competitive landscape.

Requirements

  • Bachelor’s degree in business, Marketing, Data Science, or a related field; MBA preferred.
  • Extensive B2B sales experience, ideally within the data, SaaS, or analytics domains.
  • Demonstrated success in consistently meeting or exceeding sales goals.
  • Strong knowledge of data-centric products such as APIs, data lakes, or analytics dashboards.
  • Exceptional communication, negotiation, and relationship-building skills.
  • Ability to articulate complex technical concepts in terms of business outcomes.
  • Proficiency with CRM tools (e.g., Salesforce, HubSpot).

Preferred Qualifications

  • Experience selling into industries such as fintech, marketing analytics, AdTech, or retail intelligence.
  • Proven track record working with C-suite stakeholders and large enterprise clients.
  • Familiarity with data privacy regulations like GDPR, CCPA, and other compliance standards.

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

Machine Learning Jobs at Newly Funded UK Start-ups: Q3 2025 Investment Tracker

Machine learning (ML) has become the beating heart of modern tech innovation, powering breakthroughs in healthcare, finance, cybersecurity, robotics, and more. Across the United Kingdom, this surge in ML-driven solutions is fueling the success of countless start-ups—and spurring demand for talented machine learning engineers, data scientists, and related professionals. If you’re eager to join a high-growth ML company or simply want to keep tabs on the latest trends, this Q3 2025 Investment Tracker will guide you through the newly funded UK start-ups pushing the boundaries of ML. In this article, we’ll highlight key developments from Q3 2025, delve into the most promising newly funded ventures, and shed light on the machine learning roles they’re urgently seeking to fill. Plus, we’ll show you how to connect with these employers via MachineLearningJobs.co.uk, a dedicated platform for ML job seekers. Let’s dive in!

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.

🍪 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.