Data Science Team Lead, Search & Evaluation  reference: R105207

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This review offers an in-depth look at the Data Science Team Lead, Search & Evaluation position at Elsevier, designed to help prospective candidates understand the scope, advantages, and key considerations of this impactful role.

Elsevier is at the forefront of advancing discovery and improving health outcomes by providing trusted content, data, and analytics. The organization is actively pioneering intelligent discovery experiences, leveraging cutting-edge technologies like retrieval-augmented generation (RAG), semantic search, and generative AI across their innovative platforms such as Scopus AI, LeapSpace, and ClinicalKey AI. This role sits within the Elsevier Platform Data Science organization, a pivotal team driving enterprise-scale AI, retrieval, and evaluation innovation.

Advantages for Potential Candidates:

• Impactful Leadership: This role offers a significant leadership opportunity to guide and mentor a team of data scientists and applied researchers. You'll shape the future of enterprise-wide search and retrieval excellence, directly impacting millions of users, including researchers and clinicians.
• Cutting-Edge Technology: You'll be instrumental in advancing lexical, vector, and hybrid retrieval systems, and designing robust evaluation frameworks for next-generation AI and search ecosystems. This includes working with state-of-the-art techniques like RAG, dense embeddings, neural re-ranking, and cross-encoder models.
• Strategic Influence: As a key member of the team, you will define and execute the roadmap for AI discovery capabilities, partnering closely with product, engineering, and data platform leaders. You'll also represent Elsevier in cross-functional initiatives at an enterprise level.
• Rich Data and Domains: The opportunity to work with vast scholarly, clinical, and biomedical data offers a unique chance to integrate complex structured and unstructured information, including knowledge graphs and scientific ontologies, into AI-powered discovery pipelines.
• Focus on Responsible AI: A strong emphasis is placed on building a culture of rigorous experimentation, measurable impact, and transparent science, with a commitment to Elsevier's Responsible AI standards, including fairness and bias detection.
• Career Development and Wellbeing: Elsevier is committed to employee growth and wellbeing, offering flexible working hours, comprehensive benefits, generous vacation, and various wellbeing initiatives to support both professional and personal goals.

Key Considerations for Candidates:

• Deep Technical Expertise Required: A strong academic background (PhD or MSc) in a relevant field is essential, coupled with at least 6 years of experience in building and evaluating search, ranking, or retrieval systems. This includes a minimum of 2 years in a leadership or senior technical capacity.
• Hands-On Technical Skills: Proficiency in Python and experience with key libraries and frameworks such as PyTorch, Hugging Face, LangGraph, or Haystack are crucial for success in this role.
• Evaluation Framework Development: A proven track record of building scalable evaluation frameworks and delivering measurable improvements in retrieval or generation quality is a significant requirement. This includes understanding both traditional IR metrics and GenAI-specific measures like factual consistency and hallucination rates.
• Domain Knowledge: While not strictly mandatory, familiarity with scientific ontologies and metadata standards, and prior experience in academic publishing, research intelligence, or enterprise-scale AI systems are highly preferred and will give candidates a distinct advantage.
• Collaboration and Communication: The role demands strong communication and stakeholder management skills, with the ability to effectively bridge the gap between data science, engineering, and product teams.

This Data Science Team Lead, Search & Evaluation position at Elsevier presents a compelling opportunity for experienced data science leaders looking to make a substantial impact in the advancement of scientific and healthcare discovery. If you are passionate about building intelligent systems, leading talented teams, and shaping the future of information retrieval, this role offers a challenging and rewarding career path.