Data Scientist

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