Data Science Team Lead (AI)

TL;DR

Data Science Team Lead, Search & Evaluation (AI): Leading a team of applied scientists to advance lexical, vector, and hybrid retrieval systems for hirify.global's global platforms with an accent on designing robust evaluation frameworks and shaping the next-generation AI ecosystem. Focus on developing retrieval-augmented generation (RAG) systems, optimizing search pipelines, and integrating ethical evaluation into AI systems for millions of users.

Location: Hybrid in Amsterdam or London

Company

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

What you will do

• Lead and mentor a team of data scientists and applied researchers focused on search, retrieval, and evaluation.
• Define and execute the roadmap for enterprise-wide search and retrieval excellence for academic and life sciences discovery tools.
• Design and optimize lexical, vector-based, and hybrid search architectures using dense embeddings, neural re-ranking, and cross-encoder models.
• Advance retrieval-augmented generation (RAG) systems that integrate LLMs with structured and unstructured data.
• Define and own the evaluation framework for retrieval and generative AI systems, combining traditional IR metrics with GenAI-specific measures.
• Collaborate with domain experts to integrate scientific taxonomies and structured data into AI-powered discovery pipelines.

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 or senior technical 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.
• Prior experience in academic publishing, research intelligence, or enterprise-scale AI systems.

Culture & Benefits

• Flexible working hours to help fit everything in and work when you are most productive.
• Comprehensive Pension Plan and generous vacation entitlement, with an option for sabbatical leave.
• Maternity, Paternity, Adoption, and Family Care leave.
• Home, office, or commuting allowance.
• Personal Choice budget and various employee discounts.
• Internal communities and networks, along with an Employee Assistance Program.