This is a remote position.

We are looking for a Data Science Lead to join a high-impact AI programme operating within a strictly regulated pharmaceutical environment. The role focuses on leading the machine learning and GenAI architecture behind a production-grade compliance platform that automates regulatory validation of marketing materials. This is a strategic, enterprise-scale initiative requiring strong ownership, architectural thinking, and hands-on depth in LLM-driven systems.

Responsibilities

  • Design and evolve AI and ML architecture supporting compliance validation workflows
  • Design and optimise LLM-driven retrieval and validation pipelines (RAG-based systems)
  • Own evaluation frameworks, benchmarking strategies, and continuous improvement loops
  • Implement explainability and traceability mechanisms aligned with regulatory standards
  • Collaborate closely with ML Engineers and Backend teams on productionisation of AI components
  • Drive decisions around embeddings, vector databases, and retrieval strategies
  • Ensure reproducible, testable, and high-quality AI workflows
  • Support scaling the platform into an enterprise-grade AI solution
  • Lead technical discussions across product, engineering, and compliance stakeholders

Requirements

  • Strong hands-on background in Data Science and applied Machine Learning
  • Proven experience designing and deploying LLM-based systems in production
  • Practical experience with Retrieval Augmented Generation architectures
  • Experience with vector databases and embedding pipelines
  • Strong Python expertise and familiarity with modern AI frameworks
  • Experience designing model evaluation and validation frameworks
  • Ability to operate in regulated or compliance-heavy environments
  • Strong ownership mindset and ability to influence architectural decisions
  • Confident communication skills in cross-functional environments
Nice to have
  • Experience in pharmaceutical, healthcare, or other regulated industries
  • Exposure to explainable AI methodologies or frameworks
  • Experience with document intelligence and NLP-heavy pipelines
  • Background in enterprise-scale AI platforms rather than proof-of-concept environments

Benefits

  • Solid, competitive salary
  • Work in a multinational environment on international projects
  • Comprehensive healthcare
  • Long-term B2B contract with a stable project pipeline
  • Fully remote working model