Lead Data Scientist

This position will lead the development of sophisticated search, retrieval, and reasoning systems built on large?scale datasets and advanced modelling techniques. You will act as the senior technical authority architecting platforms, shaping long?term strategy, and mentoring a high?calibre team across both Data Science and AI Engineering.

The role blends deep research, hands?on modelling, system design, and leadership. Expect to define the roadmap for how information is indexed, retrieved, ranked, explored, and transformed into actionable outcomes. This is a position for someone who enjoys building from first principles, driving technical direction, and delivering complex AI capabilities end?to?end.

WHAT YOU'LL LEAD

• Designing and building advanced retrieval, ranking, and AI?driven research systems
• Setting the technical strategy and multi?year roadmap for search, knowledge exploration, and agentic reasoning capabilities
• Architecting large?scale pipelines combining embeddings, traditional search methods, knowledge graphs, and hybrid retrieval techniques
• Developing conversational exploration tools, structured reasoning systems, and intelligent query?understanding models
• Acting as the principal technical contributor on high?impact projects, while also coaching and elevating senior engineers and scientists
• Collaborating with product and engineering to translate open?ended problem statements into clear, scalable technical plans
• Establishing best practices across experimentation, modelling, evaluation, and model lifecycle management
• Bringing cutting?edge research (LLMs, retrieval, agentic behaviours, multimodal embeddings, etc.) into production environments
• Leading workshops, technical discussions, and internal knowledge?building initiatives

• 7+ years' experience in applied Data Science or AI research within a production?focused environment
• Background in search/retrieval, ranking systems, embeddings, or related areas
• Expertise in building and scaling RAG pipelines, hybrid retrieval architectures, or advanced indexing strategies
• Strong ability to design and evaluate multimodal embedding models, vector?based retrieval, and graph?driven systems
• Deep experience with ranking and reranking architectures (bi?encoders, cross?encoders, multi?tower structures)
• Strong Python engineering fundamentals and experience deploying complex AI systems
• Experience with reasoning frameworks, orchestration approaches, or agentic system design
• Ability to guide high?impact initiatives from ideation through to production release
• Strong communication skills and the ability to influence technical and non?technical stakeholders

NICE TO HAVE

• Research publications or recognised contributions to AI/ML/NLP communities
• Experience in fine?tuning or post?training large models
• Familiarity with evaluation methods for complex retrieval and agentic systems
• Experience working with large?scale cloud environments and MLOps frameworks
• Proven ability to transition research prototypes into stable, enterprise?grade products

• Competitive compensation
• Ownership of a foundational AI capability within a rapidly scaling technical environment
• Autonomy to shape long?term direction, architecture, and technical standards
• Opportunity to work on complex, meaningful challenges with a highly skilled AI team