Data Pre Sales Consultant - Remote

City of London
2 months ago
Applications closed

Related Jobs

View all jobs

Data Engineer

Principal Data Science Consultant with Marketing Expertise

Principal Data Science Consultant - Financial Services Expertise

Principal Data Science Consultant - Financial Services Expertise

Senior Data Consultant

Lead Data Engineer - Manchester - Hybrid - £75k - £80k

Pre-Sales Data Consultant - Fully Remote - £110k - £125k (25% bonus)

This role will play a critical role in driving the success of the sales team by providing technical data-focused expertise, solutions consulting, and strategic guidance during the sales process. This individual will work closely with Business Development Managers and potential clients to understand their specific business needs and demonstrate how my clients products or services can provide value. The role requires a balance of technical (data) knowledge, communication skills, and a strong ability to build relationships, with the ultimate goal of closing high-value sales.

Salary & Benefits

Competitive salary of £80k - £95k
Fully remote working
25% annual bonus
Commission pay
Life insurance
Company pensionRole & Responsibilities

Collaborate with the sales team to understand customer requirements, pain points, and objectives.
Provide in-depth technical consultation to clients to help identify the right solutions to meet their business needs.
Conduct product demos, presentations, and workshops tailored to specific customer requirements.
Offer guidance on best practices, technical features, and value propositions of the company's solutions.
Support the sales team in the preparation and submission of RFPs and RFIs (Request for Information).
Collaborate with internal stakeholders (e.g., product development, engineering, and marketing teams) to create tailored proposals and solution architectures.
Ensure that all pre-sales documentation, proposals, and demonstrations align with the client's needs and company goals.
Deliver highly engaging and persuasive product demonstrations to prospective customers.
Tailor presentations and demo content to address specific customer pain points and objectives.
Respond to detailed technical questions, articulating how our solutions can solve the client's business challenges.What do I need to apply for the role

A minimum of three years' experience in a pre-sales role
Understanding of effective business solution delivery using the Microsoft BI toolset
Essential: Data Bricks or Delta Lake
Azure data Platform
Azure Data Factory
Azure Synapse
Power BI
SSAS
SSIS
SSRS
Communication skills
Data development process
Technical understanding (data engineering and machine learning)
Evaluate data management architectural options
Highly technical and analytical

My client have very limited interview slots and they are looking to fill this vacancy within the next 2 weeks. I have limited slots for 1st stage interviews next week so if you're interest, get in touch ASAP with a copy of your most up to date CV and email me at or call me on (phone number removed).

Please Note: This is a permanent role for UK residents only. This role does not offer Sponsorship. You must have the right to work in the UK with no restrictions. Some of our roles may be subject to successful background checks including a DBS and Credit Check.

Nigel Frank are the go-to recruiter for Power BI and Azure Data Platform roles in the UK, offering more opportunities across the country than any other. We're the proud sponsor and supporter of SQLBits, Power Platform World Tour, the London Power BI User Group, Newcastle Power BI User Group and Newcastle Data Platform and Cloud User Group. To find out more and speak confidentially about your job search or hiring needs, please contact me directly at

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.

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!

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.

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.