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

Apply Now

Data Scientist

Hertford
23 hours ago
Create job alert

Data Scientist / Data Analyst

We are seeking a talented and hands-on Data Scientist / Data Analyst to join our team. In this role, you will be instrumental in modernising how we handle and analyse our business data. You'll bridge the gap between our legacy on-premises systems and a modern cloud-based data architecture, enabling real-time, data-driven decision-making across the organisation. The ideal candidate will also have strong experience with large language models (LLMs) and machine learning (ML), which are central to the analytical capabilities we are building. This role includes deploying agentic workflows to automate and enhance decision-making processes.

Key Responsibilities:

  • Legacy System Integration: Work with existing SQL-based backend systems (e.g., Redbook 10, Sage 200, Sage CRM) running on virtualized infrastructure in a private cloud. Design and implement lightweight coding solutions to integrate and transfer data from these legacy systems into cloud-based data lakes or warehouses.

  • Cloud Data Solutions and Visualization: Migrate and organize data within platforms like Microsoft Fabric. Develop and maintain Power BI dashboards to provide real-time insights and analytics, helping the senior leadership team and other stakeholders make informed decisions.

  • Technical and Analytical Expertise: Use your coding and data analysis skills to streamline data flows and improve efficiency. Bring at least 2–3 years of real-world experience in a similar environment, along with a relevant university-level qualification.

    Skills and Experience Required:

  • Proven experience with SQL-based systems in a virtualized private cloud.

  • Ability to build lightweight integrations and interfaces to move data from legacy systems to modern cloud data solutions.

  • Hands-on experience with data visualization tools such as Power BI.

  • Strong analytical and problem-solving skills, and the ability to translate business requirements into actionable data insights.

  • Experience with large language models (LLMs) and machine learning (ML) is an advantage as well as practical experience in deploying agentic workflows for automated, intelligent data processing and analysis

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist - Outside IR35

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.

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

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.