Data Science Team Lead, Search & Evaluation (AI)

TL;DR

Data Science Team Lead (AI): Leading a team focused on advancing lexical, vector, and hybrid retrieval systems and designing evaluation frameworks to enhance hirify.global's next-generation search and AI ecosystem. Focus on building capabilities that power discovery experiences for millions of users, from researchers to clinicians.

Location: Remote

Company

hirify.global is a global leader in information and analytics, helping researchers and healthcare professionals advance science and improve health outcomes for the benefit of society.

What you will do

• Lead and mentor a team of data scientists and applied researchers focused on search, retrieval, and evaluation across hirify.global’s platforms.
• Define and execute the roadmap for enterprise-wide search and retrieval excellence, supporting the development of current and next-generation discovery tools.
• Design and optimise lexical search pipelines for large-scale scholarly, clinical, and biomedical data retrieval.
• Develop vector-based and hybrid architectures using dense embeddings and neural re-ranking to enhance retrieval precision.
• Define and own the evaluation framework for retrieval and generative AI systems, combining traditional IR metrics with GenAI-specific measures.

Requirements

• PhD or MSc in Computer Science, Data Science, Information Retrieval, or a related field.
• 6+ years of experience building and evaluating search, ranking, or retrieval systems, including 2+ years in a leadership role.
• Deep expertise in lexical search, vector retrieval, and RAG system design.
• Strong programming proficiency in Python, with hands-on experience in PyTorch, Hugging Face, LangGraph or Haystack.
• Proven record of building scalable evaluation frameworks and delivering measurable improvements in retrieval or generation quality.

Nice to have

• Experience deploying retrieval-enhanced LLMs and hybrid retrieval pipelines in production environments.
• Familiarity with scientific ontologies and metadata standards (e.g., MeSH, UMLS, ORCID, CrossRef).
• Strong communication and stakeholder management skills, with the ability to bridge data science, engineering, and product domains.
• Prior experience in academic publishing, research intelligence, or enterprise-scale AI systems.

Culture & Benefits

• Promote a healthy work/life balance across the organisation.
• Offer flexible working hours.
• Provide a comprehensive pension plan.
• Offer generous vacation entitlement and option for sabbatical leave.
• Provide flexible working hours.