Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Presales Engineer

staq
Leeds
8 months ago
Applications closed

Related Jobs

View all jobs

Lead Data engineer

Data Engineering Manager, London

Data Engineer

Senior Data Engineer

Senior Data Engineer - Reply

Principal Azure Data Engineer (Databricks)

Exciting Opportunity for aCustomer Solutions Engineer!


Our client, a leader in simulation and training data solutions, is on a mission to transform how simulation and training are delivered. Their cutting-edge product empowers customers by turning simulation data into actionable insights that drive human performance.


As demand for their product grows, they are seeking a passionate Customer Solutions Engineer who has strong experience with data and discuss the value of data, analytics and performance metrics very quickly with their potential customers. This is a customer-facing position and will involve being on-site with clients.


What will you be doing? ‍ ‍

  • Working closely with Sales, Business Development, and Product teams to strengthen and grow customer relationships.
  • Delivering technical demonstrations that highlight how our client’s solutions can effectively solve customer challenges and create value.
  • Crafting and implementing tailoredpre- and post-salesstrategies to enhance the overall customer experience.
  • Providing expert guidance on best practices for integrating and utilizing our client’s products.
  • Evaluating customer needs and designing customized solutions that meet their requirements.
  • Collaborating with the product team to ensure the successful delivery of large-scale, complex technical sales projects.
  • Building rapport with end users to understand their needs and drive demand for the product.
  • Establishing connections at all organizational levels within major aerospace and defense companies.
  • Assisting in the development of proposals and working with internal teams to secure new business opportunities.


What are we looking for?

  • 2-3 years of experience in sales, business development, or a related role in technical software or engineering services.
  • Experience in one or more technical areas, such as data science, data engineering, or cloud architecture.
  • Experience in customer-facing positions where you worked on-site with potential and current clients.
  • Proven success working with top Aerospace & Defense companies or industries like data, cloud, or AI.
  • Strong communication, analytical, and interpersonal skills.
  • A bachelor’s degree in a relevant field or equivalent professional experience.


Why join our client?

  • Competitive compensation package with annual benchmarking to ensure above-average pay.
  • 4% pension contribution to help secure your future.
  • 25 days of paid annual leave plus public holidays.
  • Comprehensive private medical insurance and mental health support through an Employee Assistance Scheme.
  • Flexible working options, including hybrid and flexitime arrangements.
  • Paid sick leave to ensure peace of mind.
  • A 5G SIM card and hardware package.
  • Be part of a forward-thinking team driving innovation and excellence in a dynamic and fast-paced environment!

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.

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.