We are looking for Data Scientists to join a long-term delivery programme focused on building production-grade AI and Generative AI solutions for enterprise customers. This is a hands-on role centred on real delivery and customer-facing systems, covering classical machine learning, advanced analytics, and LLM-based workflows including RAG. The environment is execution-driven, engineering-focused, and oriented towards measurable business impact

Responsibilities

• Design, develop, and deliver data-driven and AI-based solutions for enterprise use cases
  
• Translate business problems into robust data science and machine learning approaches
  
• Prepare, clean, and analyse structured and unstructured data
  
• Perform feature engineering and select appropriate modelling techniques
  
• Build, train, evaluate, and optimise machine learning models using Python or R
  
• Develop proof-of-concepts and evolve them into production-ready solutions
  
• Implement and improve Generative AI solutions, including RAG and LLM-based pipelines
  
• Evaluate model outputs and continuously improve quality, relevance, and reliability
  
• Contribute to technical design discussions and solution architecture
  
• Collaborate closely with engineers, product teams, and customer stakeholders
  

• Strong academic background in Data Science, Mathematics, Statistics, Computer Science, or similar
  
• Hands-on experience building end-to-end machine learning pipelines
  
• Very good practical knowledge of Python or R and common data science libraries
  
• Solid understanding of statistics and core machine learning concepts
  
• Practical experience with Generative AI, LLMs, and RAG approaches
  
• Ability to write clean, production-ready, and maintainable code
  
• Experience working in multidisciplinary delivery teams
  
• Strong communication skills in English
  
  Nice to have
  
  
• Experience with distributed data processing or Spark
  
• Exposure to deep learning frameworks such as TensorFlow or Keras
  
• Experience working in cloud-based environments
  
• Experience in fast-paced or delivery-focused project environments